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<header>
<div class="header-logo">NVIDIA CUDA-X — Complete Reference</div>
<h1>CUDA-X Libraries & APIs</h1>
<div class="total-badge">403 Libraries, APIs, Sub-Components & Tools — 22 Categories</div>
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<div class="legend-item"><div class="legend-dot" style="background:#76b900"></div>Math</div>
<div class="legend-item"><div class="legend-dot" style="background:#4da6ff"></div>Deep Learning</div>
<div class="legend-item"><div class="legend-dot" style="background:#ffaa00"></div>Data Science</div>
<div class="legend-item"><div class="legend-dot" style="background:#cc66ff"></div>Image/Video</div>
<div class="legend-item"><div class="legend-dot" style="background:#00cccc"></div>Communication</div>
<div class="legend-item"><div class="legend-dot" style="background:#cccc00"></div>Scientific</div>
<div class="legend-item"><div class="legend-dot" style="background:#ff66aa"></div>Quantum</div>
<div class="legend-item"><div class="legend-dot" style="background:#00cc88"></div>Parallel Algo</div>
<div class="legend-item"><div class="legend-dot" style="background:#ff8800"></div>Physics</div>
<div class="legend-item"><div class="legend-dot" style="background:#99cc00"></div>Partner</div>
<div class="legend-item"><div class="legend-dot" style="background:#ff6644"></div>Framework</div>
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// 1. CUDA MATH LIBRARIES
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// ═══════════════════════════════════════
// 2. SCIENTIFIC COMPUTING
// ═══════════════════════════════════════
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// ═══════════════════════════════════════
// 3. PHYSICS LIBRARIES
// ═══════════════════════════════════════
{ name:"NVIDIA Warp", cat:"physics", en:"Python framework for GPU physics simulation", ur:"Physics, robotics aur AI simulations Python mein likhna — GPU automatically use hoga", badges:["python","free"], installed:false },
{ name:"Warp — Kernels", cat:"physics", en:"GPU kernel functions in Python", ur:"Python mein GPU code likhna jaise CUDA C++ mein — bohot easy", badges:["python"], installed:false },
{ name:"Warp — Differentiable Simulation", cat:"physics", en:"Gradients through physics simulations", ur:"Physics simulation se seedha AI train karo — robotics ke liye game changer", badges:["python"], installed:false },
{ name:"Warp — Mesh Operations", cat:"physics", en:"3D mesh-based physics", ur:"3D objects ke saath collision aur physics simulate karna", badges:["python"], installed:false },
{ name:"PhysicsNeMo", cat:"physics", en:"AI physics model training framework", ur:"Physics ke AI models train karna — climate, fluid, structural engineering ke liye", badges:["python","free"], installed:false },
{ name:"PhysicsNeMo — PDE Solver", cat:"physics", en:"Physics-informed neural networks", ur:"AI se partial differential equations solve karna — engineering ka bada kaam", badges:["python"], installed:false },
{ name:"NVIDIA Earth-2", cat:"physics", en:"Weather and climate AI simulation", ur:"Duniya ke mausam aur climate ka AI se simulation — future weather predict karna", badges:["cloud","free"], installed:false },
{ name:"Earth-2 — CorrDiff", cat:"physics", en:"Diffusion model for weather downscaling", ur:"Global weather model se local level prediction nikalna — shehar ka mausam batana", badges:["python"], installed:false },
{ name:"Earth-2 — FourCastNet", cat:"physics", en:"Fourier-based weather forecasting", ur:"Fourier transform use karke agle din ka mausam predict karna — 1000x faster", badges:["python"], installed:false },
// ═══════════════════════════════════════
// 4. QUANTUM COMPUTING LIBRARIES
// ═══════════════════════════════════════
{ name:"cuQuantum", cat:"quantum", en:"GPU-accelerated quantum computing simulation", ur:"Quantum computers ko normal GPU pe simulate karna — researchers ke liye", badges:["python","free"], installed:false },
{ name:"cuQuantum — cuStateVec", cat:"quantum", en:"Quantum state vector simulation", ur:"Quantum bits (qubits) ki state simulate karna — quantum algorithms test karo", badges:["python"], installed:false },
{ name:"cuQuantum — cuTensorNet", cat:"quantum", en:"Tensor network simulation", ur:"Quantum circuits ko tensor networks ke zariye simulate karna — bade quantum systems", badges:["python"], installed:false },
{ name:"cuQuantum — cuDensityMat", cat:"quantum", en:"Density matrix simulation", ur:"Noisy quantum systems simulate karna — real quantum computer jaisi", badges:["python"], installed:false },
{ name:"cuPQC", cat:"quantum", en:"Post-quantum cryptography SDK", ur:"Future quantum computers se encryption bachane ke algorithms — next-gen security", badges:["cpp"], installed:false },
{ name:"cuPQC — CRYSTALS-Kyber", cat:"quantum", en:"Lattice-based key encapsulation", ur:"Quantum-safe key exchange — secure communication ke liye", badges:["cpp"], installed:false },
{ name:"cuPQC — CRYSTALS-Dilithium", cat:"quantum", en:"Quantum-safe digital signatures", ur:"Quantum computers se na tutne wale digital signature — files authenticate karna", badges:["cpp"], installed:false },
{ name:"CUDA-Q QEC", cat:"quantum", en:"Quantum error correction simulation", ur:"Quantum computers ki galatiyan theek karne ke algorithms simulate karna", badges:["python"], installed:false },
{ name:"CUDA-Q Solvers", cat:"quantum", en:"Hybrid quantum-classical optimization", ur:"Quantum aur classical computing milake optimization problems solve karna", badges:["python"], installed:false },
{ name:"CUDA-Q — VQE Solver", cat:"quantum", en:"Variational quantum eigensolver", ur:"Molecules ki energy calculate karna quantum se — drug design ke liye", badges:["python"], installed:false },
// ═══════════════════════════════════════
// 5. DEEP LEARNING CORE
// ═══════════════════════════════════════
{ name:"cuDNN", cat:"dl", en:"GPU library for deep neural networks", ur:"Neural networks ke building blocks — convolution, RNN, attention sab yahan hain", badges:["installed","cpp"], installed:true },
{ name:"cuDNN — Convolution", cat:"dl", en:"Forward/backward convolution for CNNs", ur:"Image recognition ke liye convolution layer — GPU pe bohot tez", badges:["cpp"], installed:true },
{ name:"cuDNN — RNN/LSTM", cat:"dl", en:"Recurrent and LSTM operations", ur:"Text aur time-series ke liye — language models ka buniyad", badges:["cpp"], installed:true },
{ name:"cuDNN — Attention (MHA)", cat:"dl", en:"Multi-head attention for transformers", ur:"ChatGPT jaisi models ka core mechanism — bohot important", badges:["cpp"], installed:true },
{ name:"cuDNN — Normalization", cat:"dl", en:"Batch/layer/group normalization", ur:"Neural network training stable rakhna — normalize karna", badges:["cpp"], installed:true },
{ name:"cuDNN — Pooling", cat:"dl", en:"Max/avg pooling operations", ur:"Feature maps ko chhota karna — CNN mein use hota hai", badges:["cpp"], installed:true },
{ name:"cuDNN — Activation", cat:"dl", en:"ReLU, Sigmoid, Tanh, GELU etc.", ur:"Neural network ke activation functions GPU pe chalana", badges:["cpp"], installed:true },
{ name:"cuDNN — Dropout", cat:"dl", en:"Stochastic neuron dropping for regularization", ur:"Training mein randomly neurons band karna — overfitting rokne ke liye", badges:["cpp"], installed:true },
{ name:"cuDNN — Softmax", cat:"dl", en:"Probability distribution output", ur:"Classification model ka output probabilities mein convert karna", badges:["cpp"], installed:true },
{ name:"TensorRT", cat:"dl", en:"High-performance inference optimizer", ur:"Trained AI model ko deploy karte waqt 10x fast chalana — production ke liye", badges:["installed","cpp","python"], installed:true },
{ name:"TensorRT — Builder", cat:"dl", en:"Builds optimized TensorRT engine", ur:"PyTorch/ONNX model le kar optimize TensorRT engine banao", badges:["cpp","python"], installed:true },
{ name:"TensorRT — Engine", cat:"dl", en:"Optimized inference runtime", ur:"Optimize hone ke baad model chalana — bohot tez inference", badges:["cpp"], installed:true },
{ name:"TensorRT — ONNX Parser", cat:"dl", en:"Parse ONNX models for TRT", ur:"ONNX format model ko TensorRT mein import karna", badges:["cpp","python"], installed:true },
{ name:"TensorRT — INT8 Quantization", cat:"dl", en:"8-bit precision for faster inference", ur:"Model ki accuracy thodi kam karo, speed 4x zyada — mobile/edge ke liye", badges:["python"], installed:true },
{ name:"TensorRT — FP16 Mode", cat:"dl", en:"Half-precision floating point inference", ur:"16-bit precision — full accuracy ke saath 2x faster", badges:["cpp","python"], installed:true },
{ name:"TensorRT-LLM", cat:"dl", en:"Optimized LLM inference library", ur:"ChatGPT jaisi badi language models deploy karna — Llama, Mistral, GPT sab chalao", badges:["python","free"], installed:false },
{ name:"TensorRT-LLM — In-flight Batching", cat:"dl", en:"Dynamic request batching for LLMs", ur:"Alag alag users ke requests ek saath efficiently chalana — server pe deploy karte waqt", badges:["python"], installed:false },
{ name:"TensorRT-LLM — KV Cache", cat:"dl", en:"Key-value cache management", ur:"LLM mein pehle compute ho chuka kaam yaad rakhna — inference fast hoti hai", badges:["python"], installed:false },
{ name:"CUTLASS", cat:"dl", en:"C++ templates for high-performance GPU kernels", ur:"Custom GPU kernels likhne ke liye modular C++ library — khud ka kernel banana ho to", badges:["cpp","free"], installed:false },
{ name:"CUTLASS — GEMM Kernels", cat:"dl", en:"Matrix multiplication with Tensor Core support", ur:"Custom matrix multiply kernel Tensor Cores pe — maximum speed ke liye", badges:["cpp"], installed:false },
{ name:"CUTLASS — Epilogue", cat:"dl", en:"Post-GEMM fused operations", ur:"Matrix multiply ke baad activation, bias add sab ek hi step mein", badges:["cpp"], installed:false },
{ name:"CUTLASS — Convolution", cat:"dl", en:"Forward/backward conv kernels", ur:"Custom convolution GPU kernels — CNN ke liye", badges:["cpp"], installed:false },
{ name:"FlashInfer", cat:"dl", en:"GPU kernels for LLM inference optimization", ur:"Large language models ki attention aur MoE operations super fast karna", badges:["python","free"], installed:false },
{ name:"FlashInfer — FlashAttention", cat:"dl", en:"Memory-efficient attention mechanism", ur:"Attention computation GPU memory efficient tarike se karna — Llama/GPT ke liye", badges:["python"], installed:false },
{ name:"FlashInfer — MoE Kernels", cat:"dl", en:"Mixture of Experts GPU kernels", ur:"Mixtral jaisi MoE models ke expert routing fast karna", badges:["python"], installed:false },
// ═══════════════════════════════════════
// 6. PARALLEL ALGORITHM LIBRARIES
// ═══════════════════════════════════════
{ name:"Thrust", cat:"parallel", en:"C++ STL-like GPU parallel algorithms", ur:"C++ STL jaisi syntax se GPU parallel algorithms likhna — sort, scan, transform etc.", badges:["cpp","installed"], installed:true },
{ name:"Thrust — device_vector", cat:"parallel", en:"GPU-resident vector container", ur:"GPU pe C++ vector — data GPU memory mein rakho seedha", badges:["cpp"], installed:true },
{ name:"Thrust — transform", cat:"parallel", en:"Parallel per-element transformation", ur:"Ek saath sab elements pe function lagao — GPU pe parallel", badges:["cpp"], installed:true },
{ name:"Thrust — sort / sort_by_key", cat:"parallel", en:"Parallel GPU sorting", ur:"Bade array ko GPU pe milliseconds mein sort karna", badges:["cpp"], installed:true },
{ name:"Thrust — reduce / transform_reduce", cat:"parallel", en:"Parallel reduction operations", ur:"Sab elements ka sum/max/min ek saath nikalna — GPU pe", badges:["cpp"], installed:true },
{ name:"Thrust — scan (prefix sum)", cat:"parallel", en:"Inclusive and exclusive prefix scan", ur:"Running total nikalna — GPU parallel processing ka basic building block", badges:["cpp"], installed:true },
{ name:"Thrust — partition", cat:"parallel", en:"Conditional data partitioning", ur:"Kisi condition ke hisaab se data do groups mein baantna", badges:["cpp"], installed:true },
{ name:"Thrust — copy_if / remove_if", cat:"parallel", en:"Conditional copy and removal", ur:"Sirf woh elements copy karo jo condition poori karein", badges:["cpp"], installed:true },
{ name:"CUB", cat:"parallel", en:"Low-level cooperative GPU primitives", ur:"Block aur warp level GPU operations — Thrust se bhi neeche ka level, zyada control", badges:["cpp","installed"], installed:true },
{ name:"CUB — DeviceReduce", cat:"parallel", en:"Device-wide reduction", ur:"Puri GPU memory pe reduction operation — sum, max, min", badges:["cpp"], installed:true },
{ name:"CUB — DeviceScan", cat:"parallel", en:"Device-wide prefix scan", ur:"Puri GPU memory pe prefix sum", badges:["cpp"], installed:true },
{ name:"CUB — DeviceSort", cat:"parallel", en:"Radix sort for entire device", ur:"Puri GPU pe radix sort — sabse fast GPU sort algorithm", badges:["cpp"], installed:true },
{ name:"CUB — BlockReduce", cat:"parallel", en:"Thread-block level reduction", ur:"Ek block ke andar sab threads milke reduce karte hain", badges:["cpp"], installed:true },
{ name:"CUB — WarpReduce", cat:"parallel", en:"Warp-level reduction primitives", ur:"32 threads (ek warp) milke reduce karte hain — sabse low level", badges:["cpp"], installed:true },
{ name:"CUB — DeviceHistogram", cat:"parallel", en:"Parallel histogram computation", ur:"Image ya data ka histogram GPU pe banana — photography/CV mein use", badges:["cpp"], installed:true },
{ name:"cuda.parallel", cat:"parallel", en:"Python parallel primitives (CCCL)", ur:"Python se GPU sort, scan, reduce chalao — NumPy se zyada tez", badges:["python","free"], installed:false },
{ name:"cuda.compute", cat:"parallel", en:"Python device-level algorithms", ur:"Python se low-level GPU algorithms — CUDA C++ jaisi power Python mein", badges:["python","free"], installed:false },
// ═══════════════════════════════════════
// 7. DATA PROCESSING LIBRARIES
// ═══════════════════════════════════════
{ name:"cuDF", cat:"data", en:"GPU-accelerated DataFrame library (Pandas replacement)", ur:"Pandas wala kaam GPU pe — same code, 100x zyada speed! Data science ka superhero", badges:["python","free"], installed:false },
{ name:"cuDF — Series", cat:"data", en:"GPU-resident 1D data column", ur:"Ek column ka data GPU pe — Pandas Series ki tarah", badges:["python"], installed:false },
{ name:"cuDF — DataFrame", cat:"data", en:"GPU table with multiple columns", ur:"Puri table GPU pe — Excel jaisi, lekin bohot tez", badges:["python"], installed:false },
{ name:"cuDF — GroupBy", cat:"data", en:"Split-apply-combine on GPU", ur:"Data ko groups mein baanto, har group pe kaam karo — SQL GROUP BY jaisi", badges:["python"], installed:false },
{ name:"cuDF — merge / join", cat:"data", en:"GPU-accelerated table joins", ur:"Do tables join karna — SQL JOIN GPU pe, microseconds mein", badges:["python"], installed:false },
{ name:"cuDF — Rolling Window", cat:"data", en:"Moving average and rolling stats", ur:"Time series ka moving average nikalna — finance/sensor data ke liye", badges:["python"], installed:false },
{ name:"cuDF — IO (CSV/Parquet/JSON)", cat:"data", en:"Fast file reading into GPU", ur:"Files seedhi GPU mein load karna — CPU mein load karne se 10x fast", badges:["python"], installed:false },
{ name:"cuDF — Polars Backend", cat:"data", en:"Use Polars syntax with GPU acceleration", ur:"Polars likhte ho? GPU pe chalega automatically — zero code change", badges:["python"], installed:false },
{ name:"cuML", cat:"data", en:"GPU scikit-learn replacement", ur:"Scikit-learn wala ML GPU pe — same API, GPU speed!", badges:["python","free"], installed:false },
{ name:"cuML — LinearRegression", cat:"data", en:"GPU linear regression", ur:"Seedhi line se prediction — house price predict karna etc.", badges:["python"], installed:false },
{ name:"cuML — RandomForest", cat:"data", en:"GPU random forest classifier/regressor", ur:"Kai decision trees milake prediction — bohot accurate ML model", badges:["python"], installed:false },
{ name:"cuML — KMeans", cat:"data", en:"GPU K-means clustering", ur:"Data ko groups mein baantna — customers segment karna etc.", badges:["python"], installed:false },
{ name:"cuML — DBSCAN", cat:"data", en:"Density-based clustering on GPU", ur:"Arbitrary shape ke clusters dhundna — anomaly detection ke liye", badges:["python"], installed:false },
{ name:"cuML — UMAP", cat:"data", en:"Dimensionality reduction visualization", ur:"Bade data ko 2D/3D mein visualize karna — data explore karne ke liye", badges:["python"], installed:false },
{ name:"cuML — HDBSCAN", cat:"data", en:"Hierarchical DBSCAN clustering", ur:"DBSCAN ka behtar version — automatic cluster count determine karta hai", badges:["python"], installed:false },
{ name:"cuML — SVM", cat:"data", en:"Support Vector Machine on GPU", ur:"Classification ke liye classic algorithm — GPU pe bohot fast", badges:["python"], installed:false },
{ name:"cuML — PCA", cat:"data", en:"Principal Component Analysis on GPU", ur:"Data ke main features nikalna — dimensionality reduce karna", badges:["python"], installed:false },
{ name:"cuML — NearestNeighbors", cat:"data", en:"GPU k-nearest neighbors", ur:"Query point ke sabse nazdik k points dhundna — recommendation systems ke liye", badges:["python"], installed:false },
{ name:"cuVS", cat:"data", en:"GPU vector search library", ur:"Semantic search aur vector databases ke liye — AI chatbot ke peeche yahi hota hai", badges:["python","free"], installed:false },
{ name:"cuVS — CAGRA", cat:"data", en:"GPU-native graph-based nearest neighbor", ur:"World's fastest vector search algorithm — GPU native hai isliye super tez", badges:["python"], installed:false },
{ name:"cuVS — IVF-Flat", cat:"data", en:"Inverted file index (exact)", ur:"Vectors ko groups mein baanto aur exact search karo", badges:["python"], installed:false },
{ name:"cuVS — IVF-PQ", cat:"data", en:"Inverted file + product quantization", ur:"Vectors compress karke bade datasets pe fast search — RAM bachao", badges:["python"], installed:false },
{ name:"cuVS — Brute Force", cat:"data", en:"Exact exhaustive search", ur:"Har vector check karo — small datasets pe sab se accurate", badges:["python"], installed:false },
{ name:"cuGraph", cat:"data", en:"GPU graph analytics (NetworkX replacement)", ur:"Facebook, Twitter jaisi social networks analyze karna — GPU pe NetworkX", badges:["python","free"], installed:false },
{ name:"cuGraph — PageRank", cat:"data", en:"Google's page ranking algorithm on GPU", ur:"Web pages rank karna — Google ka wahi algorithm GPU pe", badges:["python"], installed:false },
{ name:"cuGraph — BFS / SSSP", cat:"data", en:"Breadth-first and shortest path search", ur:"Graph mein shortest path dhundna — maps aur networks ke liye", badges:["python"], installed:false },
{ name:"cuGraph — Louvain", cat:"data", en:"Community detection algorithm", ur:"Social network mein friend groups dhundna — community detection", badges:["python"], installed:false },
{ name:"cuGraph — Triangle Counting", cat:"data", en:"Count triangles in graph", ur:"Graph mein triangles count karna — social network clustering coefficient", badges:["python"], installed:false },
{ name:"cuOpt", cat:"data", en:"GPU optimization engine for routing problems", ur:"Delivery routes, logistics optimize karna — Amazon/FedEx jaisi companies use karti hain", badges:["python","free"], installed:false },
{ name:"cuOpt — VRP Solver", cat:"data", en:"Vehicle routing problem solver", ur:"Kai gadiyon ke routes optimize karna — delivery companies ke liye", badges:["python"], installed:false },
{ name:"cuOpt — TSP Solver", cat:"data", en:"Traveling salesman problem", ur:"Ek gadi ke liye sabse chhota route dhundna", badges:["python"], installed:false },
{ name:"NeMo Curator", cat:"data", en:"Data curation for LLM training", ur:"LLM train karne ke liye data clean aur prepare karna — quality data = better AI", badges:["python","free"], installed:false },
{ name:"NeMo Curator — Text Dedup", cat:"data", en:"Remove duplicate training data", ur:"Same text baar baar AI ko na sikhao — duplicates hatao", badges:["python"], installed:false },
{ name:"NeMo Curator — Quality Filter", cat:"data", en:"Score and filter low-quality text", ur:"Kharab quality ka text hatao — AI better seekhe", badges:["python"], installed:false },
{ name:"NeMo Curator — Synthetic Data", cat:"data", en:"Generate synthetic training data", ur:"AI se AI ka training data banana — data ki kami poori karo", badges:["python"], installed:false },
{ name:"Morpheus", cat:"data", en:"Real-time cybersecurity AI pipeline", ur:"Real-time mein cyber attacks detect karna — network traffic AI se analyze karna", badges:["python","free"], installed:false },
{ name:"nvComp", cat:"data", en:"GPU-accelerated compression library", ur:"Data ko GPU pe compress/decompress karna — storage aur transfer fast karo", badges:["cpp","free"], installed:false },
{ name:"nvComp — LZ4", cat:"data", en:"Fast LZ4 compression on GPU", ur:"Tez compression — speed priority ho to", badges:["cpp"], installed:false },
{ name:"nvComp — Snappy", cat:"data", en:"Google Snappy on GPU", ur:"Google ka compression algorithm GPU pe", badges:["cpp"], installed:false },
{ name:"nvComp — GDeflate", cat:"data", en:"GPU-optimized deflate compression", ur:"ZIP jaisa compression GPU pe — storage bachat ke liye", badges:["cpp"], installed:false },
{ name:"nvComp — Cascaded", cat:"data", en:"High-ratio GPU compression", ur:"Maximum compression ratio — storage aur bandwidth bachao", badges:["cpp"], installed:false },
{ name:"GPU Direct Storage (GDS)", cat:"data", en:"Direct NVMe-to-GPU data path", ur:"Hard drive se seedha GPU memory mein data aao — CPU bypass karo, 2x fast", badges:["cpp"], installed:false },
{ name:"Dask-CUDA", cat:"data", en:"Multi-GPU Dask integration", ur:"RAPIDS ko kai GPUs aur machines pe scale karna — big data ke liye", badges:["python","free"], installed:false },
// ═══════════════════════════════════════
// 8. IMAGE & VIDEO LIBRARIES
// ═══════════════════════════════════════
{ name:"nvImageCodec", cat:"img", en:"GPU image encoding/decoding framework", ur:"Images GPU pe decode/encode karna — AI training mein data loading 10x fast", badges:["cpp","python","free"], installed:false },
{ name:"nvJPEG", cat:"img", en:"GPU-accelerated JPEG codec", ur:"JPEG images GPU pe decode karna — ML training mein lakh images jaldi load karo", badges:["cpp"], installed:false },
{ name:"nvJPEG2000", cat:"img", en:"GPU JPEG2000 codec", ur:"Medical imaging (DICOM) aur digital cinema ke liye JPEG2000 GPU pe", badges:["cpp"], installed:false },
{ name:"nvTIFF", cat:"img", en:"GPU TIFF image decoder", ur:"TIFF format (scientific/geospatial) images GPU pe fast decode karna", badges:["cpp"], installed:false },
{ name:"nvBMP", cat:"img", en:"GPU BMP codec", ur:"BMP format images GPU pe decode karna", badges:["cpp"], installed:false },
{ name:"NVIDIA DALI", cat:"img", en:"GPU data loading and preprocessing pipeline", ur:"AI training ke liye images/video/audio fast load karo GPU pe — CPU bottleneck hatao", badges:["python","free"], installed:false },
{ name:"DALI — Pipeline", cat:"img", en:"Declarative data preprocessing graph", ur:"Image processing steps define karo — DALI automatically GPU pe chalayega", badges:["python"], installed:false },
{ name:"DALI — RandomCrop", cat:"img", en:"Random image cropping augmentation", ur:"Training mein random crop — AI ko diverse views sikhao", badges:["python"], installed:false },
{ name:"DALI — ColorJitter", cat:"img", en:"Random color augmentation", ur:"Images ka color randomly badlo — AI robust ho", badges:["python"], installed:false },
{ name:"DALI — Resize / Normalize", cat:"img", en:"GPU resize and normalization", ur:"Images resize aur normalize karna — AI input prepare karna", badges:["python"], installed:false },
{ name:"DALI — Video Reader", cat:"img", en:"GPU video loading and decoding", ur:"Video files GPU pe decode karna — video AI ke liye", badges:["python"], installed:false },
{ name:"CV-CUDA", cat:"img", en:"GPU computer vision preprocessing", ur:"Camera se aata image AI se pehle process karna — real-time vision AI pipeline", badges:["cpp","python","free"], installed:false },
{ name:"CV-CUDA — cvtColor", cat:"img", en:"Color space conversion", ur:"RGB to BGR, RGB to HSV etc. — GPU pe super fast", badges:["python"], installed:false },
{ name:"CV-CUDA — Resize", cat:"img", en:"GPU image resizing", ur:"Images ka size change karna GPU pe — ek saath lakhon images", badges:["python"], installed:false },
{ name:"CV-CUDA — Normalize", cat:"img", en:"Per-channel normalization", ur:"Image pixels normalize karna — AI input ke liye zaroor", badges:["python"], installed:false },
{ name:"CV-CUDA — Warp/Rotate", cat:"img", en:"Geometric transformations", ur:"Image ghumana aur transform karna GPU pe", badges:["python"], installed:false },
{ name:"cuCIM", cat:"img", en:"Medical and scientific image processing", ur:"Medical images (MRI, CT) aur satellite images analyze karna — healthcare AI", badges:["python","free"], installed:false },
{ name:"cuCIM — Stain Normalization", cat:"img", en:"Histology slide color normalization", ur:"Medical microscope images ka color normalize karna — cancer detection AI ke liye", badges:["python"], installed:false },
{ name:"NPP (Performance Primitives)", cat:"img", en:"GPU image and signal processing primitives", ur:"2D image processing ke blocks — filter, resize, color convert sab GPU pe", badges:["cpp","installed"], installed:true },
{ name:"NPP — Filter Operations", cat:"img", en:"Gaussian, box, median filters", ur:"Image blur, sharpen, noise remove karna GPU pe", badges:["cpp"], installed:true },
{ name:"NPP — Color Conversion", cat:"img", en:"RGB, YUV, HSV conversions", ur:"Image color format badalna — video processing mein zaroor", badges:["cpp"], installed:true },
{ name:"NPP — Morphological ops", cat:"img", en:"Erode, dilate, open, close", ur:"Image mein shapes dhundna aur refine karna — medical imaging", badges:["cpp"], installed:true },
{ name:"NPP — Histogram", cat:"img", en:"GPU image histogram", ur:"Image ke pixels ka distribution calculate karna — exposure adjust karna", badges:["cpp"], installed:true },
{ name:"NPP — Threshold", cat:"img", en:"Image thresholding", ur:"Pixels ko condition ke hisaab se black/white karna — object detect karna", badges:["cpp"], installed:true },
{ name:"NVIDIA Video Codec SDK", cat:"img", en:"Hardware video encode/decode", ur:"Video GPU hardware pe encode/decode karna — streaming servers aur editors ke liye", badges:["cpp","free"], installed:false },
{ name:"Video Codec — NVDEC", cat:"img", en:"Hardware video decoder", ur:"H.264/H.265/AV1 video hardware pe decode karna — CPU zero use", badges:["cpp"], installed:false },
{ name:"Video Codec — NVENC", cat:"img", en:"Hardware video encoder", ur:"Video record/stream GPU hardware pe encode karna — OBS, streaming apps use karti hain", badges:["cpp"], installed:false },
{ name:"Video Codec — NVJPEG Enc", cat:"img", en:"Hardware JPEG encoding", ur:"JPEG images bohot fast encode karna hardware pe", badges:["cpp"], installed:false },
{ name:"NVIDIA Optical Flow SDK", cat:"img", en:"Pixel motion detection between frames", ur:"Video mein ek frame se doosre mein pixels kitna hile — video compression aur tracking", badges:["cpp","free"], installed:false },
{ name:"Optical Flow — NvOFAPI", cat:"img", en:"Optical flow computation API", ur:"GPU hardware optical flow calculate karna — hardware accelerated", badges:["cpp"], installed:false },
// ═══════════════════════════════════════
// 9. COMMUNICATION LIBRARIES
// ═══════════════════════════════════════
{ name:"NCCL", cat:"comm", en:"Multi-GPU/multi-node collective communication", ur:"Kai GPUs ek network pe ek saath kaam karein — distributed AI training ka core", badges:["cpp","python","free"], installed:false },
{ name:"NCCL — AllReduce", cat:"comm", en:"Sum/average across all GPUs", ur:"Sab GPUs ke gradients ek mein mila do — distributed training mein zaroor", badges:["cpp"], installed:false },
{ name:"NCCL — Broadcast", cat:"comm", en:"One GPU to all GPUs", ur:"Ek GPU se baaki sab ko data bhejno", badges:["cpp"], installed:false },
{ name:"NCCL — AllGather", cat:"comm", en:"Gather data from all GPUs to all", ur:"Har GPU apna data sab ko de do", badges:["cpp"], installed:false },
{ name:"NCCL — ReduceScatter", cat:"comm", en:"Reduce then scatter to GPUs", ur:"Sab ka data ek jagah mila kar phir distribute karo — large model training", badges:["cpp"], installed:false },
{ name:"NCCL — Send/Recv", cat:"comm", en:"Point-to-point GPU communication", ur:"Do GPUs ke darmiyan seedha data transfer", badges:["cpp"], installed:false },
{ name:"NVSHMEM", cat:"comm", en:"OpenSHMEM for GPU cluster communication", ur:"Kai GPUs ki memory ko ek badi shared memory ki tarah use karna", badges:["cpp"], installed:false },
{ name:"NVSHMEM — put/get", cat:"comm", en:"One-sided remote memory access", ur:"Doosre GPU ki memory mein seedha likho/parho — wait karne ki zaroorat nahi", badges:["cpp"], installed:false },
{ name:"NVSHMEM — Atomic ops", cat:"comm", en:"Remote atomic operations", ur:"Doosre GPU ki memory pe atomic increment/compare — race conditions nahi", badges:["cpp"], installed:false },
{ name:"NIXL", cat:"comm", en:"Low-latency inference transfer library", ur:"LLM serving mein KV cache ek GPU/node se doosre transfer karna — latency kam karo", badges:["cpp","free"], installed:false },
{ name:"NIXL — KV Cache Transfer", cat:"comm", en:"Transfer attention KV cache between nodes", ur:"LLM ke attention cache ko nodes ke darmiyan move karna — disaggregated inference", badges:["cpp"], installed:false },
// ═══════════════════════════════════════
// 10. PARTNER LIBRARIES
// ═══════════════════════════════════════
{ name:"OpenCV (GPU)", cat:"partner", en:"Computer vision library with CUDA backend", ur:"Sabse popular computer vision library — face detection, object tracking GPU pe", badges:["cpp","python","free"], installed:false },
{ name:"OpenCV — cuda::filter2D", cat:"partner", en:"GPU convolution filter", ur:"Image par custom filter lagana GPU pe — OpenCV ka GPU version", badges:["cpp"], installed:false },
{ name:"OpenCV — cuda::pyrDown", cat:"partner", en:"GPU image pyramid", ur:"Image ko dhire dhire chhota karna — object detection ke liye", badges:["cpp"], installed:false },
{ name:"OpenCV — cuda::ORB", cat:"partner", en:"GPU feature detection", ur:"Image mein key points dhundna GPU pe — image matching ke liye", badges:["cpp"], installed:false },
{ name:"FFmpeg (GPU)", cat:"partner", en:"Video/audio framework with NVDEC/NVENC", ur:"Video convert, stream, edit karna — GPU hardware acceleration ke saath", badges:["cpp","free"], installed:false },
{ name:"ArrayFire", cat:"partner", en:"GPU matrix, signal, image processing", ur:"MATLAB jaisi syntax se GPU computing — scientists ke liye easy", badges:["cpp","python","free"], installed:false },
{ name:"MAGMA", cat:"partner", en:"GPU linear algebra for heterogeneous systems", ur:"CPU+GPU milake linear algebra — supercomputer level math", badges:["cpp","free"], installed:false },
{ name:"IMSL Fortran Library", cat:"partner", en:"Fortran numerical library with GPU support", ur:"Puraani Fortran code GPU pe chalana — legacy scientific software ke liye", badges:["cpp","paid"], installed:false },
{ name:"Gunrock", cat:"partner", en:"GPU graph processing library", ur:"Graphs GPU pe process karna — social networks, routing problems", badges:["cpp","free"], installed:false },
{ name:"CHOLMOD", cat:"partner", en:"Sparse Cholesky factorization on GPU", ur:"Physics aur engineering mein sparse matrices factorize karna", badges:["cpp","free"], installed:false },
{ name:"Triton Ocean SDK", cat:"partner", en:"Real-time ocean water simulation", ur:"Realistic paani ka simulation — games aur training simulations ke liye", badges:["cpp","paid"], installed:false },
{ name:"CUVIlib", cat:"partner", en:"GPU imaging for medical and defense", ur:"Medical, industrial aur defense imaging applications ke liye GPU library", badges:["cpp","paid"], installed:false },
{ name:"CuPy", cat:"partner", en:"NumPy/SciPy compatible GPU array library", ur:"NumPy ka code GPU pe chalao — import cupy as np karke! Zero change.", badges:["python","free"], installed:false },
{ name:"CuPy — ndarray", cat:"partner", en:"GPU n-dimensional array", ur:"NumPy array ki tarah lekin GPU pe — bohot tez", badges:["python"], installed:false },
{ name:"CuPy — cupy.linalg", cat:"partner", en:"GPU linear algebra via CuPy", ur:"NumPy linalg GPU pe — same functions, GPU speed", badges:["python"], installed:false },
{ name:"CuPy — cupy.fft", cat:"partner", en:"GPU FFT via CuPy Python", ur:"NumPy FFT GPU pe — Python se", badges:["python"], installed:false },
{ name:"CuPy — RawKernel", cat:"partner", en:"Custom CUDA kernels from Python", ur:"Python se custom GPU code likhna — CUDA C++ nahi jaante? Koi baat nahi", badges:["python"], installed:false },
// ═══════════════════════════════════════
// 11. DEVELOPER TOOLS
// ═══════════════════════════════════════
{ name:"Nsight Systems", cat:"tool", en:"Full-system GPU performance profiler", ur:"Poora system profile karo — CPU, GPU, memory sab ki timing dekho", badges:["free","installed"], installed:true },
{ name:"Nsight Compute", cat:"tool", en:"GPU kernel-level profiler", ur:"Ek specific GPU kernel ke andar kya ho raha hai dekho — optimization ke liye", badges:["free","installed"], installed:true },
{ name:"Nsight Graphics", cat:"tool", en:"GPU graphics debugger and profiler", ur:"Games aur graphics apps debug karo — har frame ka analysis", badges:["free","installed"], installed:false },
{ name:"Nsight Eclipse Edition", cat:"tool", en:"GPU debugging in Eclipse IDE", ur:"Eclipse IDE mein CUDA code debug karna", badges:["free"], installed:false },
{ name:"cuda-gdb", cat:"tool", en:"GPU debugger (GDB extended)", ur:"CUDA code step by step debug karo — breakpoints GPU kernels mein lagao", badges:["free","installed"], installed:true },
{ name:"NVIDIA Visual Profiler (nvvp)", cat:"tool", en:"Visual GPU profiling tool", ur:"GPU performance visually dekho — kahan slow hai pata chale", badges:["free"], installed:false },
{ name:"nvcc", cat:"tool", en:"NVIDIA CUDA C/C++ compiler", ur:"CUDA C++ code compile karne ka compiler — GPU code ka compiler", badges:["installed","free"], installed:true },
{ name:"nvcc — ptxas", cat:"tool", en:"PTX to SASS assembler", ur:"Intermediate GPU code ko final GPU instructions mein convert karna", badges:["installed"], installed:true },
{ name:"Compute Sanitizer", cat:"tool", en:"GPU memory error and race detector", ur:"GPU code mein memory errors aur race conditions dhundna — debug tool", badges:["free","installed"], installed:true },
{ name:"Compute Sanitizer — Memcheck", cat:"tool", en:"GPU memory access checker", ur:"Out-of-bounds memory access detect karna — crashes fix karo", badges:["free"], installed:true },
{ name:"Compute Sanitizer — Racecheck", cat:"tool", en:"GPU race condition detector", ur:"Kai threads ek saath same memory access karein to pakro", badges:["free"], installed:true },
{ name:"Compute Sanitizer — Initcheck", cat:"tool", en:"Uninitialized memory detector", ur:"Bina initialize kiye memory use karna detect karna", badges:["free"], installed:true },
{ name:"cuTile", cat:"tool", en:"Tile-based GPU programming model", ur:"GPU programming ka naya model — tiles mein sochna, tiling problems ke liye", badges:["cpp","free"], installed:false },
{ name:"CUDA Python Bindings", cat:"tool", en:"Official Python bindings for CUDA driver", ur:"Python se seedha CUDA driver API call karna — low-level GPU control", badges:["python","free"], installed:false },
{ name:"CUDA-GDB Python Integration", cat:"tool", en:"Python scripts for GPU debugging", ur:"Python se GPU debug karna — automation of debugging", badges:["free"], installed:false },
{ name:"NVML (Management Library)", cat:"tool", en:"GPU monitoring and management API", ur:"GPU temperature, fan speed, utilization check karna — monitoring tools banao", badges:["cpp","python","free","installed"], installed:true },
{ name:"nvidia-smi", cat:"tool", en:"GPU status and management CLI", ur:"Terminal se GPU status dekho — temp, memory, utilization — har developer use karta hai", badges:["free","installed"], installed:true },
{ name:"DCGM", cat:"tool", en:"Data Center GPU Manager", ur:"Server pe kai GPUs monitor karo — health check aur profiling data center mein", badges:["free"], installed:false },
{ name:"Multi-Process Service (MPS)", cat:"tool", en:"Multiple process GPU sharing", ur:"Kai processes ek GPU share karein efficiently — server pe deploy karte waqt", badges:["free","installed"], installed:true },
{ name:"CUDA Toolkit Installer", cat:"tool", en:"Complete toolkit package manager", ur:"CUDA install karne ka tool — libraries, compiler, tools sab ek saath", badges:["free","installed"], installed:true },
{ name:"NGC Container Registry", cat:"tool", en:"NVIDIA GPU Cloud container hub", ur:"Tayyar AI/ML Docker containers — seedha pull karo aur chalao", badges:["free"], installed:false },
{ name:"CUDA Compatibility Layer", cat:"tool", en:"Run newer CUDA apps on older drivers", ur:"Naya CUDA code purane driver pe chalana — backward compatibility", badges:["free","installed"], installed:true },
{ name:"PTX (Parallel Thread Execution)", cat:"tool", en:"CUDA intermediate assembly language", ur:"CUDA ka middle layer — hardware se independent instruction set", badges:["cpp"], installed:false },
{ name:"SASS (Shader Assembly)", cat:"tool", en:"GPU machine-level assembly", ur:"GPU ka actual machine code — sabse low level, hardware specific", badges:["cpp"], installed:false },
// ═══════════════════════════════════════
// 12. NEMO FRAMEWORK & MICROSERVICES
// ═══════════════════════════════════════
{ name:"NeMo Framework", cat:"nemo", en:"End-to-end LLM/multimodal AI training framework", ur:"Bade AI models (LLM, speech, vision) train karne ka poora framework — ek hi jagah sab kuch", badges:["python","free"], installed:false },
{ name:"NeMo — Megatron-Core", cat:"nemo", en:"Large-scale model parallelism training", ur:"Aisa bada AI model train karo jo ek GPU mein na aaye — kai GPUs pe parallel training", badges:["python"], installed:false },
{ name:"NeMo — SFT (Supervised Fine-Tuning)", cat:"nemo", en:"Fine-tune LLMs on custom data", ur:"Kisi bhi LLM ko apne kaam ke data se fine-tune karo — domain-specific AI banana", badges:["python"], installed:false },
{ name:"NeMo — LoRA Fine-Tuning", cat:"nemo", en:"Parameter-efficient fine-tuning", ur:"Sirf thodi parameters fine-tune karo — kam resources mein bhi kaam kare", badges:["python"], installed:false },
{ name:"NeMo — RLHF", cat:"nemo", en:"Reinforcement learning from human feedback", ur:"Human feedback se AI ko behtar banana — ChatGPT bhi isi tarike se banaya tha", badges:["python"], installed:false },
{ name:"NeMo — DPO Training", cat:"nemo", en:"Direct preference optimization", ur:"AI ko pasandida jawab dene ki training — RLHF se asaan alternative", badges:["python"], installed:false },
{ name:"NeMo — Multimodal (Image+Text)", cat:"nemo", en:"Train vision-language models", ur:"Image aur text dono samajhne wala AI model train karna — GPT-4V jaisa", badges:["python"], installed:false },
{ name:"NeMo — Speech ASR", cat:"nemo", en:"Automatic speech recognition training", ur:"Awaaz ko text mein convert karne wala AI train karna — Whisper jaisa", badges:["python"], installed:false },
{ name:"NeMo — Text-to-Speech (TTS)", cat:"nemo", en:"Speech synthesis model training", ur:"Text se awaaz banane wala AI train karna — voice cloning bhi", badges:["python"], installed:false },
{ name:"NeMo — NLP Models", cat:"nemo", en:"Named entity, classification, QA models", ur:"Text se naam/jagah nikalna, classify karna, sawaalon ke jawab dena", badges:["python"], installed:false },
{ name:"NeMo Guardrails", cat:"nemo", en:"Safety and compliance for LLMs", ur:"AI ko galat baatein karne se rokna — safe aur compliant rakho", badges:["python","free"], installed:false },
{ name:"NeMo Guardrails — Input Rails", cat:"nemo", en:"Filter harmful user inputs", ur:"User ka kharab sawal AI tak pohonchne se rokna", badges:["python"], installed:false },
{ name:"NeMo Guardrails — Output Rails", cat:"nemo", en:"Filter harmful AI outputs", ur:"AI ka jawab bahar jaane se pehle check karna — harmful content rokna", badges:["python"], installed:false },
{ name:"NeMo Guardrails — Topical Rails", cat:"nemo", en:"Keep AI on topic", ur:"AI ko sirf apne kaam ki baatein karne par majboor karna — off-topic jawab rokna", badges:["python"], installed:false },
{ name:"NeMo Evaluator", cat:"nemo", en:"Model evaluation and benchmarking", ur:"AI model kitna acha hai check karna — benchmarks pe performance measure karna", badges:["python","free"], installed:false },
{ name:"NeMo Evaluator — LLM-as-Judge", cat:"nemo", en:"Use AI to evaluate AI outputs", ur:"Ek AI se doosre AI ka jawab check karwana — automated quality assessment", badges:["python"], installed:false },
{ name:"NeMo Evaluator — Custom Datasets", cat:"nemo", en:"Evaluate on your own test data", ur:"Apna test data banao aur AI usse evaluate karo", badges:["python"], installed:false },
{ name:"NeMo Retriever", cat:"nemo", en:"RAG pipeline for enterprise search", ur:"Company ke documents se AI ko search karne dena — ChatGPT + apna data", badges:["python","free"], installed:false },
{ name:"NeMo Retriever — Embedding NIM", cat:"nemo", en:"Convert text to vector embeddings", ur:"Text ko numbers (vectors) mein convert karna — semantic search ke liye zaroor", badges:["python"], installed:false },
{ name:"NeMo Retriever — Reranking NIM", cat:"nemo", en:"Rerank search results by relevance", ur:"Search results ko relevance ke hisaab se dobara sort karna — best result upar aaye", badges:["python"], installed:false },
{ name:"NeMo Customizer", cat:"nemo", en:"Enterprise fine-tuning microservice", ur:"Enterprise level mein AI model fine-tune karna — Kubernetes pe scale hota hai", badges:["python","cloud"], installed:false },
{ name:"NeMo Curator — Text Pipeline", cat:"nemo", en:"Download, deduplicate and filter web text", ur:"Internet ka text download karo, duplicates hatao, quality filter lagao — LLM data prep", badges:["python"], installed:false },
{ name:"NeMo Curator — Image Pipeline", cat:"nemo", en:"Curate image-text paired data", ur:"Image aur text pairs ka data prepare karna — vision AI training ke liye", badges:["python"], installed:false },
{ name:"NeMo Curator — Video Pipeline", cat:"nemo", en:"Curate video training data", ur:"Video data prepare karna — video understanding AI ke liye", badges:["python"], installed:false },
// ═══════════════════════════════════════
// 13. NIM MICROSERVICES
// ═══════════════════════════════════════
{ name:"NVIDIA NIM", cat:"nim", en:"Prebuilt optimized AI inference microservices", ur:"Koi bhi AI model 5 minute mein deploy karo — sab kuch ready packed Docker container mein", badges:["cloud","python"], installed:false },
{ name:"NIM — LLM Inference", cat:"nim", en:"Deploy Llama, Mistral, GPT etc.", ur:"Open source LLMs ek click mein deploy karo — Llama 3, Mistral, Gemma sab", badges:["cloud"], installed:false },
{ name:"NIM — Embedding Models", cat:"nim", en:"Deploy text embedding APIs", ur:"Text ko vectors mein convert karne ka API — RAG ke liye zaroor", badges:["cloud"], installed:false },
{ name:"NIM — Reranking Models", cat:"nim", en:"Deploy reranker APIs", ur:"Search results rerank karne ka API — search quality improve karo", badges:["cloud"], installed:false },
{ name:"NIM — Vision Models", cat:"nim", en:"Deploy image understanding models", ur:"Images samajhne wale models deploy karo — captioning, VQA etc.", badges:["cloud"], installed:false },
{ name:"NIM — Speech Models (ASR)", cat:"nim", en:"Deploy Parakeet/Canary ASR", ur:"Speech to text models deploy karo — real-time transcription ke liye", badges:["cloud"], installed:false },
{ name:"NIM — Code Generation", cat:"nim", en:"Deploy CodeLlama, StarCoder etc.", ur:"Code likhne wale AI models deploy karo — developer tools banao", badges:["cloud"], installed:false },
{ name:"NIM — Chemistry Models", cat:"nim", en:"Deploy MolMIM, ESMFold for molecules", ur:"Molecules aur proteins ke liye AI models deploy karna — drug discovery", badges:["cloud"], installed:false },
{ name:"NIM — Digital Biology", cat:"nim", en:"AlphaFold2, protein structure prediction", ur:"Protein ki 3D shape predict karne ka API — medical research ke liye", badges:["cloud"], installed:false },
{ name:"NIM — Grounding DINO", cat:"nim", en:"Open-vocabulary object detection API", ur:"Koi bhi cheez image mein dhundho — text se describe karo aur AI dhund le", badges:["cloud"], installed:false },
{ name:"NIM — SAM 2", cat:"nim", en:"Segment Anything Model 2 API", ur:"Image mein kisi bhi object ka mask/outline dhundna — Meta ka model", badges:["cloud"], installed:false },
{ name:"NIM — Cosmos (World Models)", cat:"nim", en:"Physics-based world simulation models", ur:"Real duniya jaisa virtual environment banao — robotics training ke liye", badges:["cloud"], installed:false },
{ name:"NIM Agent Toolkit", cat:"nim", en:"Build AI agents using NIM microservices", ur:"NIM use karke AI agents banana — sochne aur kaam karne wale AI", badges:["python","free"], installed:false },
// ═══════════════════════════════════════
// 14. TRITON INFERENCE SERVER
// ═══════════════════════════════════════
{ name:"Triton Inference Server", cat:"triton", en:"Production AI model serving platform", ur:"Kai AI models ek saath serve karo — production servers ke liye standard tool", badges:["python","free"], installed:false },
{ name:"Triton — TensorRT Backend", cat:"triton", en:"Serve TensorRT optimized models", ur:"TensorRT se optimize model Triton pe deploy karna — maximum speed", badges:["cpp"], installed:false },
{ name:"Triton — PyTorch Backend", cat:"triton", en:"Serve TorchScript models", ur:"PyTorch models seedha Triton pe serve karna — no conversion needed", badges:["python"], installed:false },
{ name:"Triton — TensorFlow Backend", cat:"triton", en:"Serve TF SavedModel", ur:"TensorFlow models Triton se serve karna", badges:["python"], installed:false },
{ name:"Triton — ONNX Runtime Backend", cat:"triton", en:"Serve ONNX models", ur:"ONNX format ke models serve karna — framework agnostic", badges:["python"], installed:false },
{ name:"Triton — Python Backend", cat:"triton", en:"Custom Python preprocessing/postprocessing", ur:"Python code Triton pipeline mein lagana — custom logic add karo", badges:["python"], installed:false },
{ name:"Triton — vLLM Backend", cat:"triton", en:"High-throughput LLM serving", ur:"vLLM use karke LLMs bohot users ke liye serve karna", badges:["python"], installed:false },
{ name:"Triton — Dynamic Batching", cat:"triton", en:"Auto-batch incoming requests", ur:"Alag waqt aane wali requests ek batch mein mila do — GPU efficient use", badges:["cpp"], installed:false },
{ name:"Triton — Model Ensemble", cat:"triton", en:"Chain multiple models in pipeline", ur:"Kai models ko ek pipeline mein connect karna — preprocessing + model + postprocessing", badges:["cpp"], installed:false },
{ name:"Triton — Model Analyzer", cat:"triton", en:"Profile and optimize server config", ur:"Best batch size aur GPU count suggest karna automatically", badges:["python","free"], installed:false },
{ name:"Triton — Perf Analyzer", cat:"triton", en:"Benchmark model inference performance", ur:"Model ki speed aur latency measure karna — performance test karo", badges:["python","free"], installed:false },
{ name:"Triton — gRPC/HTTP API", cat:"triton", en:"Standard inference APIs", ur:"gRPC ya HTTP se model ko call karna — apps mein integrate karo", badges:["python"], installed:false },
{ name:"Triton — BLS (Business Logic)", cat:"triton", en:"Custom logic inside inference pipeline", ur:"Triton pipeline mein business logic likhna — Python mein", badges:["python"], installed:false },
{ name:"Triton — Model Control API", cat:"triton", en:"Load/unload models at runtime", ur:"Chalta hua server pe naye models load karo — downtime nahi", badges:["cpp"], installed:false },
{ name:"Triton — Shared Memory", cat:"triton", en:"Zero-copy data transfer to GPU", ur:"CPU-GPU data copy bypass karo — latency kam karo", badges:["cpp"], installed:false },
// ═══════════════════════════════════════
// 15. DEEPSTREAM SDK
// ═══════════════════════════════════════
{ name:"DeepStream SDK", cat:"deepstream", en:"Video analytics AI streaming pipeline", ur:"Security cameras aur CCTV ke video mein real-time AI — objects detect karo live", badges:["cpp","python","free"], installed:false },
{ name:"DeepStream — nvinfer Plugin", cat:"deepstream", en:"GPU inference plugin for GStreamer", ur:"Video stream mein AI inference lagao — GStreamer plugin", badges:["cpp"], installed:false },
{ name:"DeepStream — nvtracker Plugin", cat:"deepstream", en:"Multi-object tracking across frames", ur:"Video mein objects ko frame to frame track karna — camera mein aata jata cheez follow karo", badges:["cpp"], installed:false },
{ name:"DeepStream — nvmsgbroker", cat:"deepstream", en:"Send analytics to Kafka/MQTT/Azure", ur:"AI results ko Kafka, MQTT, cloud bhejno — IoT integration", badges:["cpp"], installed:false },
{ name:"DeepStream — nvstreammux", cat:"deepstream", en:"Multiplex multiple video streams", ur:"Kai cameras ke streams ek saath process karna — 100+ cameras ek GPU pe", badges:["cpp"], installed:false },
{ name:"DeepStream — nvdsosd Plugin", cat:"deepstream", en:"Draw bounding boxes on video", ur:"Video pe detection boxes aur labels draw karna — visualization", badges:["cpp"], installed:false },
{ name:"DeepStream — Python Bindings", cat:"deepstream", en:"DeepStream in Python", ur:"Python se DeepStream pipeline banana — C++ ki zaroorat nahi", badges:["python"], installed:false },
{ name:"DeepStream — 360 Camera Support", cat:"deepstream", en:"Fisheye and panoramic camera AI", ur:"360 degree cameras ka video AI se process karna — security ke liye", badges:["cpp"], installed:false },
{ name:"DeepStream — Triton Integration", cat:"deepstream", en:"Use Triton models in DeepStream pipeline", ur:"Triton pe chal rahe models DeepStream ke saath use karna", badges:["cpp"], installed:false },
{ name:"DeepStream — Smart Record", cat:"deepstream", en:"Event-triggered video recording", ur:"AI kuch detect kare to automatically video save ho jaye — smart recording", badges:["cpp"], installed:false },
{ name:"DeepStream — Redis Adapter", cat:"deepstream", en:"Send metadata to Redis database", ur:"DeepStream results seedha Redis mein save karna", badges:["cpp"], installed:false },
// ═══════════════════════════════════════
// 16. NVIDIA RIVA (SPEECH AI)
// ═══════════════════════════════════════
{ name:"NVIDIA Riva", cat:"riva", en:"Fully accelerated speech AI SDK", ur:"Awaaz se text, text se awaaz aur speech translate karne ka poora SDK — call centers ke liye", badges:["python","free"], installed:false },
{ name:"Riva — ASR (Speech to Text)", cat:"riva", en:"Real-time speech recognition", ur:"Bolta hua insaan sun ke text likhna — real-time transcription", badges:["python"], installed:false },
{ name:"Riva — TTS (Text to Speech)", cat:"riva", en:"Neural text-to-speech synthesis", ur:"Text parh ke awaaz mein bolna — realistic AI voice", badges:["python"], installed:false },
{ name:"Riva — Voice Activity Detection", cat:"riva", en:"Detect when someone is speaking", ur:"Koi bol raha hai ya nahi detect karna — call center bots ke liye", badges:["python"], installed:false },
{ name:"Riva — Punctuation & Capitalization", cat:"riva", en:"Post-process ASR output", ur:"Speech recognition ke baad proper punctuation aur capitals lagana", badges:["python"], installed:false },
{ name:"Riva — Speaker Diarization", cat:"riva", en:"Who spoke when in a meeting", ur:"Meeting mein kaun kab bola pata lagana — automated minutes", badges:["python"], installed:false },
{ name:"Riva — Neural MT (Translation)", cat:"riva", en:"Real-time speech translation", ur:"Ek zubaan mein bolo doosri mein translate ho jaye — real-time interpreter", badges:["python"], installed:false },
{ name:"Riva — Custom Vocabulary", cat:"riva", en:"Add domain-specific words to ASR", ur:"Medical, legal ya technical words ASR mein add karo — accuracy improve karo", badges:["python"], installed:false },
{ name:"Riva — gRPC API", cat:"riva", en:"Real-time streaming speech API", ur:"Live audio stream bhejo aur real-time text wapas pao", badges:["python"], installed:false },
// ═══════════════════════════════════════
// 17. TAO TOOLKIT (Computer Vision Training)
// ═══════════════════════════════════════
{ name:"TAO Toolkit", cat:"tao", en:"Train and fine-tune vision AI models easily", ur:"Computer vision models bina bade data ke train karna — transfer learning se", badges:["python","free"], installed:false },
{ name:"TAO — Object Detection", cat:"tao", en:"Train YOLO, DetectNet, SSD models", ur:"Images mein objects detect karne ke models train karna — security cameras ke liye", badges:["python"], installed:false },
{ name:"TAO — Image Classification", cat:"tao", en:"Train ResNet, EfficientNet classifiers", ur:"Image ko categories mein classify karne ka model train karna", badges:["python"], installed:false },
{ name:"TAO — Instance Segmentation", cat:"tao", en:"Train Mask RCNN for pixel masks", ur:"Object ke exact pixels dhundna — background remove jaisi cheez", badges:["python"], installed:false },
{ name:"TAO — Pose Estimation", cat:"tao", en:"Human body keypoint detection", ur:"Insaan ke hath, paon, sir position detect karna — gym AI, security", badges:["python"], installed:false },
{ name:"TAO — Action Recognition", cat:"tao", en:"Recognize human actions in video", ur:"Video mein insaan kya kar raha hai pata lagana — surveillance", badges:["python"], installed:false },
{ name:"TAO — License Plate Recognition", cat:"tao", en:"Detect and read number plates", ur:"Car ki number plate padhna — parking, traffic management", badges:["python"], installed:false },
{ name:"TAO — Face Detection", cat:"tao", en:"Detect and recognize faces", ur:"Faces detect karna — attendance, security ke liye", badges:["python"], installed:false },
{ name:"TAO — Optical Inspection", cat:"tao", en:"Defect detection for manufacturing", ur:"Factory mein products ki ghaltiyan AI se dhundna — quality control", badges:["python"], installed:false },
{ name:"TAO — Data Augmentation", cat:"tao", en:"Expand training data automatically", ur:"Ek image se kai variations banana — AI ko zyada data se train karo", badges:["python"], installed:false },
{ name:"TAO — Pruning", cat:"tao", en:"Remove redundant model weights", ur:"Model chhota karo without accuracy lose kiye — edge devices ke liye", badges:["python"], installed:false },
{ name:"TAO — Export to ONNX/TRT", cat:"tao", en:"Export trained model for deployment", ur:"Trained model ko TensorRT ke liye export karna — deployment ready", badges:["python"], installed:false },
// ═══════════════════════════════════════
// 18. NVIDIA ISAAC (ROBOTICS)
// ═══════════════════════════════════════
{ name:"Isaac SDK", cat:"isaac", en:"Full robotics AI development platform", ur:"Robots banane ka poora AI platform — sensors se lekar motors tak sab", badges:["cpp","python","free"], installed:false },
{ name:"Isaac — ROS 2 Integration", cat:"isaac", en:"Connect with Robot Operating System", ur:"Standard robotics middleware ke saath kaam karna — ROS 2 compatible", badges:["python"], installed:false },
{ name:"Isaac — Manipulator Arm AI", cat:"isaac", en:"Robot arm grasping and manipulation", ur:"Robot arm se cheezein pakadna aur rakhna — factory automation", badges:["python"], installed:false },
{ name:"Isaac — Navigation Stack", cat:"isaac", en:"Autonomous robot navigation", ur:"Robot khud chale seedha — obstacles avoid kare, path plan kare", badges:["cpp"], installed:false },
{ name:"Isaac — Perception (3D)", cat:"isaac", en:"3D object detection and pose estimation", ur:"3D mein objects detect karna — robot ko pata ho kya kahan hai", badges:["python"], installed:false },
{ name:"Isaac — Sim (Omniverse based)", cat:"isaac", en:"Photorealistic robot simulation", ur:"Real duniya jaisi simulation mein robot train karo — physical robot se pehle", badges:["python","free"], installed:false },
{ name:"Isaac — GROOT (Humanoid AI)", cat:"isaac", en:"Foundation model for humanoid robots", ur:"Insaan jaese robots ke liye AI model — general purpose robotic brain", badges:["python"], installed:false },
{ name:"Isaac — Dexterous Manipulation", cat:"isaac", en:"Fine motor skills for robot hands", ur:"Robot haath se pench kholna, keyboard type karna — fine movements", badges:["python"], installed:false },
{ name:"Isaac — Synthetic Data Gen", cat:"isaac", en:"Create robot training data in simulation", ur:"Real data collect kiye bina simulation se training data banana", badges:["python"], installed:false },
{ name:"Isaac — cuRobo", cat:"isaac", en:"GPU-accelerated motion planning", ur:"Robot ka aagla move GPU pe milliseconds mein plan karna", badges:["python","free"], installed:false },
// ═══════════════════════════════════════
// 19. NVIDIA OMNIVERSE
// ═══════════════════════════════════════
{ name:"NVIDIA Omniverse", cat:"omniverse", en:"Real-time 3D simulation and collaboration platform", ur:"3D duniya banao aur simulate karo — factory, building, robot sab ek jagah", badges:["python","free"], installed:false },
{ name:"Omniverse — USD (Universal Scene)", cat:"omniverse", en:"Pixar's 3D scene description format", ur:"3D scenes ka standard format — sab tools ek saath kaam karein", badges:["python"], installed:false },
{ name:"Omniverse — PhysX 5", cat:"omniverse", en:"GPU-accelerated physics simulation", ur:"Real duniya jaisi physics GPU pe — objects girna, tootna, paani behna", badges:["cpp"], installed:false },
{ name:"Omniverse — RTX Renderer", cat:"omniverse", en:"Real-time ray tracing renderer", ur:"Photorealistic 3D rendering real-time mein — product visualization", badges:["cpp"], installed:false },
{ name:"Omniverse — Digital Twin", cat:"omniverse", en:"Virtual replica of physical systems", ur:"Factory ya building ka virtual copy banao — test karo, optimize karo", badges:["python"], installed:false },
{ name:"Omniverse — Replicator", cat:"omniverse", en:"Synthetic data generation for AI", ur:"AI training ke liye 3D simulation se data banana — real data ki zaroorat nahi", badges:["python","free"], installed:false },
{ name:"Omniverse — Nucleus Server", cat:"omniverse", en:"Shared 3D asset collaboration server", ur:"Team milkar ek 3D scene pe kaam kare — real-time collaboration", badges:["free"], installed:false },
{ name:"Omniverse — Cosmos (World Foundation)", cat:"omniverse", en:"Physics-based world generation AI", ur:"Real duniya jaisi virtual duniya AI se generate karna — autonomous driving training", badges:["python"], installed:false },
{ name:"Omniverse — Drive Sim", cat:"omniverse", en:"Autonomous vehicle simulation", ur:"Self-driving cars ka test virtual duniya mein karo — accidents se pehle test", badges:["python","paid"], installed:false },
{ name:"Omniverse — Isaac Sim", cat:"omniverse", en:"Robot simulation in photorealistic 3D", ur:"Robots ko realistic simulation mein train karo — real world se pehle", badges:["python","free"], installed:false },
// ═══════════════════════════════════════
// 20. NVIDIA METROPOLIS (VIDEO ANALYTICS)
// ═══════════════════════════════════════
{ name:"NVIDIA Metropolis", cat:"metropolis", en:"Video AI platform for cities and enterprises", ur:"Smart cities, malls, factories ke cameras mein AI lagana — sab kuch monitor karo", badges:["python","free"], installed:false },
{ name:"Metropolis — VSS Blueprint", cat:"metropolis", en:"Visual AI agent for video surveillance", ur:"Hazaaron cameras ek saath AI se monitor karo — security agents", badges:["python"], installed:false },
{ name:"Metropolis — VCAT (Video Annotation)", cat:"metropolis", en:"AI-assisted video data annotation", ur:"Video data ko AI ki madad se label karna — training data banana asaan", badges:["python"], installed:false },
{ name:"Metropolis — Retail Analytics", cat:"metropolis", en:"People counting and queue detection", ur:"Mall mein kitne log hain, queue kitni lambi hai — retail AI", badges:["python"], installed:false },
{ name:"Metropolis — Traffic Analytics", cat:"metropolis", en:"Vehicle counting and speed detection", ur:"Sadak pe gadiyon ki count aur speed AI se pata lagana", badges:["python"], installed:false },
{ name:"Metropolis — Safety AI", cat:"metropolis", en:"Hardhat and PPE detection", ur:"Factory mein workers ne helmet pehna ya nahi — safety compliance AI", badges:["python"], installed:false },
// ═══════════════════════════════════════
// 21. CUDA RUNTIME & DRIVER APIS
// ═══════════════════════════════════════
{ name:"CUDA Runtime API", cat:"runtime", en:"High-level GPU programming interface", ur:"GPU se kaam karne ka main API — memory, kernels, streams sab yahan se control", badges:["cpp","installed"], installed:true },
{ name:"CUDA — cudaMalloc / cudaFree", cat:"runtime", en:"GPU memory allocation/deallocation", ur:"GPU pe memory lena aur wapas karna — sab se basic GPU operation", badges:["cpp","installed"], installed:true },
{ name:"CUDA — cudaMemcpy", cat:"runtime", en:"Copy data between CPU and GPU", ur:"CPU ka data GPU pe bhejna aur wapas lana — bohot common operation", badges:["cpp","installed"], installed:true },
{ name:"CUDA — cudaMemcpyAsync", cat:"runtime", en:"Asynchronous memory copy", ur:"Data copy aur GPU ka kaam ek saath chalao — speed double ho jaye", badges:["cpp","installed"], installed:true },
{ name:"CUDA — cudaStream", cat:"runtime", en:"Asynchronous GPU execution streams", ur:"Kai kaam GPU pe ek saath paralel chalao — streams se control karo", badges:["cpp","installed"], installed:true },
{ name:"CUDA — cudaEvent", cat:"runtime", en:"GPU timing and synchronization", ur:"GPU ka kaam kab khatam hua measure karo — profiling aur sync ke liye", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Unified Memory (cudaMallocManaged)", cat:"runtime", en:"CPU+GPU shared memory space", ur:"Ek memory CPU aur GPU dono use karein — code likhna asaan ho jata hai", badges:["cpp","installed"], installed:true },
{ name:"CUDA — cudaDeviceSynchronize", cat:"runtime", en:"Wait for GPU to finish", ur:"GPU ka kaam khatam hone ka intezaar karo — result lene se pehle zaroor", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Cooperative Groups", cat:"runtime", en:"Flexible thread group communication", ur:"GPU threads ke beech flexible communication — advanced parallel algorithms", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Graph API (cudaGraph)", cat:"runtime", en:"Record and replay GPU operations", ur:"GPU operations record karo aur baar baar replay karo — overhead kam karo", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Dynamic Parallelism", cat:"runtime", en:"GPU kernel launches another kernel", ur:"GPU se hi nayi GPU kernel launch karo — recursive parallel algorithms", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Peer-to-Peer (P2P)", cat:"runtime", en:"Direct GPU-to-GPU data transfer", ur:"Do GPUs seedha ek doosre se data exchange karein — CPU bypass karo", badges:["cpp","installed"], installed:true },
{ name:"CUDA Driver API", cat:"runtime", en:"Low-level GPU control interface", ur:"GPU ka seedha control — Runtime se bhi neeche, zyada power zyada complexity", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Texture Memory", cat:"runtime", en:"Cached read-only GPU memory", ur:"Image data ke liye special cached memory — reading fast hoti hai", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Constant Memory", cat:"runtime", en:"Broadcast cached memory for all threads", ur:"Sab threads ko ek saath same data chahiye — constant memory use karo", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Shared Memory", cat:"runtime", en:"Fast on-chip thread-block memory", ur:"Ek block ke sab threads mein share hone wali super fast memory — bottleneck hatao", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Warp-Level Primitives", cat:"runtime", en:"Fast warp shuffle operations", ur:"32 threads (warp) ke beech data seedha share karo — bohot fast communication", badges:["cpp","installed"], installed:true },
{ name:"CUDA — L2 Cache Persistence", cat:"runtime", en:"Pin data in L2 cache", ur:"Kuch data hamesha L2 cache mein rakho — baar baar access karna fast hoga", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Virtual Memory Management", cat:"runtime", en:"Fine-grained GPU memory control", ur:"GPU memory ko manually manage karo — advanced use cases ke liye", badges:["cpp","installed"], installed:true },
{ name:"CUDA — Multicast Memory", cat:"runtime", en:"One write visible to multiple GPUs", ur:"Ek jagah likho kai GPUs mein dikh jaye — multi-GPU efficiency", badges:["cpp"], installed:false },
// ═══════════════════════════════════════
// 23. CUDA-X AI ENTERPRISE & MISC
// ═══════════════════════════════════════
{ name:"NVIDIA AI Enterprise", cat:"tool", en:"Full enterprise AI software suite", ur:"Companies ke liye poora AI stack — support, security, updates ke saath", badges:["paid"], installed:false },
{ name:"CUDA-X Healthcare", cat:"sci", en:"GPU AI for medical imaging and genomics", ur:"Hospital aur research ke liye GPU AI — cancer detect karo, DNA analyze karo", badges:["paid"], installed:false },
{ name:"Clara Parabricks", cat:"sci", en:"GPU genomics pipeline (DNA analysis)", ur:"Insaan ka DNA analyze karna — 50x faster than CPU — cancer research, ancestry", badges:["python","free"], installed:false },
{ name:"Clara Parabricks — HaplotypeCaller", cat:"sci", en:"GPU genetic variant calling", ur:"DNA mein mutations dhundna — genetic disease diagnosis", badges:["python"], installed:false },
{ name:"Clara Parabricks — BWA-MEM2", cat:"sci", en:"GPU DNA sequence alignment", ur:"DNA sequences ko reference genome se match karna", badges:["python"], installed:false },
{ name:"Clara Parabricks — DeepVariant", cat:"sci", en:"Deep learning variant detection", ur:"AI se DNA mutations accurately detect karna", badges:["python"], installed:false },
{ name:"cuDF — String Operations", cat:"data", en:"GPU string processing (regex, split, join)", ur:"Text data GPU pe process karna — regex, split, replace — Python pandas jaisa", badges:["python"], installed:false },
{ name:"cuDF — Time Series", cat:"data", en:"GPU datetime operations", ur:"Dates aur times ke saath kaam GPU pe — finance aur sensor data ke liye", badges:["python"], installed:false },
{ name:"CUDA — warp-level matrix (WMMA)", cat:"runtime", en:"Warp-level tensor core operations", ur:"32 threads milke ek saath matrix multiply karein Tensor Cores pe — maximum speed", badges:["cpp","installed"], installed:true },
{ name:"NVTX (NVIDIA Tools Extension)", cat:"tool", en:"Custom annotations in profiler", ur:"Apne code mein labels lagao jo profiler mein dikhen — debugging asaan karo", badges:["cpp","python","free","installed"], installed:true },
{ name:"cuBLAS — Batched GEMM", cat:"math", en:"Multiple matrix multiplications at once", ur:"Ek saath saikdon matrix multiply karo — batch training mein zaroor kaam aata hai", badges:["cpp"], installed:false },
{ name:"Holoscan SDK", cat:"sci", en:"Real-time medical AI streaming platform", ur:"Hospital mein real-time AI — surgery ke dauran live analysis, ultrasound AI etc.", badges:["python","free"], installed:false },
{ name:"Holoscan — Sensor Bridge", cat:"sci", en:"Medical device data ingestion", ur:"Medical sensors aur cameras se real-time data lana AI pipeline mein", badges:["cpp"], installed:false },
{ name:"Holoscan — Inference Manager", cat:"sci", en:"Multi-model inference orchestration", ur:"Kai AI models ek saath real-time chalana — medical diagnosis", badges:["python"], installed:false },
{ name:"NVIDIA FLARE", cat:"dl", en:"Federated learning framework", ur:"Data ek jagah ikhatta kiye bina kai hospitals ka AI milke train karna — privacy safe", badges:["python","free"], installed:false },
{ name:"FLARE — FedAvg Algorithm", cat:"dl", en:"Federated averaging for model weights", ur:"Sab hospitals ke model weights average karo — centralized training jaisi accuracy", badges:["python"], installed:false },
{ name:"FLARE — Differential Privacy", cat:"dl", en:"Privacy-preserving federated learning", ur:"Training mein individual data bilkul private rahe — GDPR compliant AI", badges:["python"], installed:false },
{ name:"cuNumeric", cat:"partner", en:"Drop-in NumPy replacement on GPU cluster", ur:"NumPy code likho — cuNumeric automatically GPU cluster pe chalaye — zero change", badges:["python","free"], installed:false },
{ name:"nvJitLink", cat:"tool", en:"GPU JIT (just-in-time) linker library", ur:"GPU code runtime pe link karna — dynamic kernel loading", badges:["cpp","installed"], installed:false },
{ name:"CUDA — Profiling APIs (CUPTI)", cat:"tool", en:"CUDA Profiling Tools Interface", ur:"Apne code mein profiling data collect karo — custom performance tools banana", badges:["cpp","free","installed"], installed:true },
{ name:"NvBench", cat:"tool", en:"GPU microbenchmarking framework", ur:"GPU code ki speed accurately measure karna — kernels benchmark karo", badges:["cpp","free"], installed:false },
{ name:"CUDA — Async Memops API", cat:"runtime", en:"Hardware-accelerated async memory operations", ur:"GPU memory operations hardware se asynchronously chalana — maximum overlap", badges:["cpp"], installed:false },
{ name:"cuStreamz", cat:"data", en:"GPU streaming data processing", ur:"Real-time stream data GPU pe process karna — Kafka + cuDF integration", badges:["python","free"], installed:false },
{ name:"PyTorch (CUDA backend)", cat:"framework", en:"Most popular deep learning framework", ur:"Sabse popular AI framework — Python mein neural networks banao GPU pe", badges:["python","free"], installed:false },
{ name:"PyTorch — torch.cuda", cat:"framework", en:"CUDA device management in PyTorch", ur:"PyTorch mein GPU control — .cuda() se GPU pe bhejna", badges:["python"], installed:false },
{ name:"PyTorch — torch.amp", cat:"framework", en:"Automatic mixed precision training", ur:"FP16/BF16 aur FP32 mix karke training fast karo — autocast use karo", badges:["python"], installed:false },
{ name:"PyTorch — DataParallel", cat:"framework", en:"Multi-GPU data parallel training", ur:"Ek model kai GPUs pe chalao — training fast karo", badges:["python"], installed:false },
{ name:"PyTorch — DistributedDataParallel", cat:"framework", en:"Multi-node distributed training", ur:"Kai machines pe AI train karo — bade models ke liye", badges:["python"], installed:false },
{ name:"PyTorch — torch.compile", cat:"framework", en:"JIT compilation for GPU kernels", ur:"PyTorch code automatically optimize karo — 2-3x speed up ho sakta hai", badges:["python"], installed:false },
{ name:"TensorFlow (CUDA backend)", cat:"framework", en:"Google's deep learning framework", ur:"Google ka AI framework — GPU pe automatically chalata hai", badges:["python","free"], installed:false },
{ name:"TensorFlow — tf.distribute", cat:"framework", en:"Multi-GPU distribution strategy", ur:"TensorFlow training kai GPUs pe distribute karna", badges:["python"], installed:false },
{ name:"TensorFlow — XLA", cat:"framework", en:"Accelerated linear algebra compiler", ur:"TensorFlow graph JIT compile karna — GPU pe optimize code", badges:["python"], installed:false },
{ name:"JAX (CUDA backend)", cat:"framework", en:"NumPy on GPU with auto-differentiation", ur:"NumPy jaisa syntax, GPU speed, automatic gradients — research ke liye perfect", badges:["python","free"], installed:false },
{ name:"JAX — jit", cat:"framework", en:"JIT compilation for GPU kernels", ur:"Python function GPU ke liye compile karo — 100x speed up", badges:["python"], installed:false },
{ name:"JAX — vmap", cat:"framework", en:"Automatic vectorization", ur:"Ek function ek saath kai inputs pe chalao — loops nahi likhne", badges:["python"], installed:false },
{ name:"JAX — pmap", cat:"framework", en:"Parallel execution across GPUs", ur:"Ek saath kai GPUs pe automatically chalao", badges:["python"], installed:false },
{ name:"Numba (CUDA JIT)", cat:"framework", en:"JIT-compile Python for GPU", ur:"Python function GPU pe chalao — @cuda.jit decorator lagao bas", badges:["python","free"], installed:false },
{ name:"Numba — @cuda.jit", cat:"framework", en:"Python function as GPU kernel", ur:"Normal Python function GPU kernel ban jata hai — bohot easy GPU programming", badges:["python"], installed:false },
{ name:"Numba — cuda.to_device", cat:"framework", en:"Copy array from CPU to GPU", ur:"NumPy array GPU pe bhejna — Numba se", badges:["python"], installed:false },
{ name:"Triton (OpenAI)", cat:"framework", en:"Python GPU kernel writing language", ur:"Python mein GPU kernels likhna — CUDA C++ se asaan, PyTorch se zyada control", badges:["python","free"], installed:false },
{ name:"Triton — @triton.jit", cat:"framework", en:"Triton kernel decorator", ur:"Python function GPU kernel declare karna Triton mein", badges:["python"], installed:false },
{ name:"RAPIDS Suite", cat:"framework", en:"End-to-end GPU data science", ur:"cuDF + cuML + cuGraph + cuVS milake poora data science pipeline GPU pe", badges:["python","free"], installed:false },
{ name:"RAPIDS — cuDF-Pandas", cat:"framework", en:"Drop-in Pandas GPU accelerator", ur:"import cudf.pandas activate karo — Pandas automatically GPU pe chalega!", badges:["python"], installed:false },
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