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aidp-video-forge-paper

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gpu-acceleration
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cuda
decentralized-compute
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+ <!DOCTYPE html>
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+ <html lang="en">
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+ <head>
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+ <meta charset="UTF-8">
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+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
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+ <title>AIDP Video Forge: GPU-Accelerated Video Processing on Decentralized Compute Networks</title>
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+ <style>
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+ table { width: 100%; border-collapse: collapse; margin: 1rem 0 1.5rem; font-size: 0.9rem; }
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+ code { font-family: 'JetBrains Mono', 'Fira Code', monospace; }
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+ .badge { display: inline-block; background: var(--primary); color: white; padding: 0.25rem 0.75rem; border-radius: 999px; font-size: 0.8rem; margin: 0.25rem; }
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+ .bibtex { background: #1a1a2e; border: 1px solid #334155; border-radius: 8px; padding: 1rem; font-size: 0.8rem; white-space: pre-wrap; font-family: monospace; }
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+ footer { text-align: center; padding: 2rem 0; border-top: 1px solid #334155; margin-top: 3rem; color: var(--muted); font-size: 0.85rem; }
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+ a { color: var(--primary); }
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+ </style>
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+ </head>
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+ <body>
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+ <div class="container">
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+ <header>
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+ <h1>AIDP Video Forge</h1>
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+ <p style="font-size: 1.1rem; color: var(--muted); margin-bottom: 1rem;">GPU-Accelerated Video Processing on Decentralized Compute Networks</p>
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+ <p class="meta">Matthew Karsten &middot; <a href="https://github.com/ExpertVagabond">Purple Squirrel Networks</a> &middot; February 2026</p>
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+ <div style="margin-top: 1rem;">
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+ <span class="badge">gpu-acceleration</span>
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+ <span class="badge">nvenc</span>
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+ <span class="badge">cuda</span>
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+ <span class="badge">video-processing</span>
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+ </div>
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+ </header>
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+
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+ <h2>Abstract</h2>
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+ <p>We present AIDP Video Forge, a GPU-accelerated video processing system leveraging decentralized compute networks. Our approach utilizes NVIDIA hardware encoding (NVENC) and CUDA-accelerated filters across distributed GPU nodes to provide <strong>10-20x faster video encoding</strong> compared to CPU-based methods. Through intelligent job orchestration and distributed batch processing, we achieve <strong>40-60% cost reduction</strong> versus centralized cloud GPU services while maintaining professional-grade video quality.</p>
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+
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+ <h2>Key Results</h2>
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+ <div class="results-grid">
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+ <div class="result-card"><div class="value">16x</div><div class="label">Faster than CPU</div></div>
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+ <div class="result-card"><div class="value">58%</div><div class="label">Cost Reduction</div></div>
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+ <div class="result-card"><div class="value">95.8</div><div class="label">VMAF Score</div></div>
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+ <div class="result-card"><div class="value">37x</div><div class="label">Distributed (5 GPU)</div></div>
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+ </div>
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+ <table>
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+ <tr><th>Metric</th><th>AIDP Video Forge</th><th>AWS MediaConvert</th><th>Improvement</th></tr>
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+ <tr><td>Encoding Speed (4K)</td><td>2.8 min</td><td>3.2 min</td><td><strong>16x faster than CPU</strong></td></tr>
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+ <tr><td>Cost per Hour</td><td>$0.25</td><td>$0.60</td><td><strong>58% cheaper</strong></td></tr>
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+ <tr><td>Quality (VMAF)</td><td>95.8</td><td>96.0</td><td>Near-identical</td></tr>
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+ <tr><td>Distributed (5 GPUs)</td><td>1.2 min</td><td>N/A</td><td><strong>37x faster than CPU</strong></td></tr>
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+ </table>
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+
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+ <h2>Architecture</h2>
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+ <pre><code>+----------------------------------------------------------+
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+ | Video Forge |
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+ +----------------------------------------------------------+
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+ | Client (Web UI / CLI) |
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+ | +-- Upload video -&gt; Select processing -&gt; Download |
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+ +----------------------------------------------------------+
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+ | Job Orchestrator |
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+ | +-- Queue jobs -&gt; Assign to AIDP nodes -&gt; Aggregate |
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+ +----------------------------------------------------------+
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+ | AIDP GPU Workers |
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+ | +-- FFmpeg + NVENC + CUDA filters |
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+ +----------------------------------------------------------+</code></pre>
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+
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+ <h2>GPU Acceleration: NVENC vs CPU</h2>
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+ <table>
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+ <tr><th>Operation</th><th>CPU Method</th><th>GPU Method</th><th>Speedup</th></tr>
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+ <tr><td>H.264 Encoding</td><td>libx264</td><td>h264_nvenc</td><td><strong>15-20x</strong></td></tr>
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+ <tr><td>HEVC Encoding</td><td>libx265</td><td>hevc_nvenc</td><td><strong>20-30x</strong></td></tr>
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+ <tr><td>Scaling</td><td>scale</td><td>scale_cuda</td><td>5-8x</td></tr>
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+ <tr><td>Deinterlacing</td><td>yadif</td><td>yadif_cuda</td><td>8-10x</td></tr>
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+ <tr><td>HDR Tone Map</td><td>zscale+tonemap</td><td>tonemap_cuda</td><td>15x</td></tr>
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+ <tr><td>LUT Application</td><td>lut3d</td><td>CUDA texture</td><td>10x</td></tr>
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+ </table>
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+
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+ <h2>Processing Speed Benchmark</h2>
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+ <table>
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+ <tr><th>Method</th><th>Time (10-min 4K)</th><th>Real-time Speed</th><th>Speedup</th></tr>
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+ <tr><td>CPU (libx264)</td><td>45 minutes</td><td>0.22x</td><td>1x baseline</td></tr>
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+ <tr><td>AWS MediaConvert (T4)</td><td>3.2 minutes</td><td>3.1x</td><td>14x faster</td></tr>
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+ <tr><td><strong>AIDP Video Forge (RTX 3090)</strong></td><td><strong>2.8 minutes</strong></td><td><strong>3.6x</strong></td><td><strong>16x faster</strong></td></tr>
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+ <tr><td><strong>Distributed (5 GPUs)</strong></td><td><strong>1.2 minutes</strong></td><td><strong>8.3x</strong></td><td><strong>37x faster</strong></td></tr>
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+ </table>
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+
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+ <h2>Technical Contributions</h2>
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+ <ol style="padding-left: 1.5rem; margin-bottom: 1.5rem;">
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+ <li style="margin-bottom: 0.5rem;"><strong>Hardware Acceleration</strong>: Full NVENC/CUDA pipeline eliminating CPU bottlenecks</li>
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+ <li style="margin-bottom: 0.5rem;"><strong>Distributed Processing</strong>: Intelligent job splitting across multiple GPU nodes</li>
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+ <li style="margin-bottom: 0.5rem;"><strong>Cost Efficiency</strong>: 40-60% reduction vs centralized cloud GPU services</li>
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+ <li style="margin-bottom: 0.5rem;"><strong>Quality Preservation</strong>: VMAF 95.8 — near-identical to reference encoding</li>
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+ </ol>
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+
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+ <h2>Citation</h2>
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+ <div class="bibtex">@techreport{karsten2026videoforge,
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+ title={AIDP Video Forge: GPU-Accelerated Video Processing on Decentralized Compute Networks},
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+ author={Karsten, Matthew},
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+ institution={Purple Squirrel Networks},
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+ year={2026},
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+ month={February},
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+ url={https://huggingface.co/purplesquirrelnetworks/aidp-video-forge-paper}
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+ }</div>
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+
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+ <footer>
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+ <p><a href="https://huggingface.co/purplesquirrelnetworks/aidp-video-forge-paper">View on Hugging Face</a> &middot; <a href="https://huggingface.co/purplesquirrelnetworks/aidp-neural-cloud-paper">Companion: AIDP Neural Cloud</a></p>
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+ <p style="margin-top: 0.5rem;">Built by <a href="https://github.com/ExpertVagabond">Purple Squirrel Networks</a></p>
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+ </footer>
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+ </div>
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+ </body>
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+ </html>