Air-Gapped Batch Inference & Zero-Cloud-Cost Pipeline Engine

Core Technical Evidence: 10,000,000 Batch Benchmark

The following performance logs are physical measurements executed at Matsubara Longevity Science Research Institute (Kanagawa, Japan). Cloud-managed services fail under large-scale batch workloads due to unbounded memory fragmentation (Exit 137 OOM) and prohibitive API costs. This infrastructure locks resource consumption into O(1) constant space while executing 10 million offline batch inferences.

Deterministic Benchmark Summary

Metric	Measured Value	Operational State
Total Inferences Completed	10,000,000 / 10,000,000	100.00% Success Rate (0.00% Error)
Consecutive Verification	2 of 2 full runs completed	Identical runtime and zero divergence
Total Runtime	10.9 Hours (39,240 s)	Continuous unattended execution
Average Throughput	254.9 req/s	Fully stabilized cruising velocity
Host RAM Footprint	6.7 GiB to 9.4 GiB	Strictly bounded in O(1) constant space
Swap Memory Allocation	0 Bytes (0B)	Zero paging overhead, zero disk thrashing
Persistence Integrity	3.4 GB SQLite WAL	`PRAGMA integrity_check: ok`
Cloud Infrastructure Cost	$0.00 USD	Complete air-gapped execution

Physical Hardware Topology (HP Z4 G4 Fortress)

Compute Base: HP Z4 G4 Workstation
Processor: Intel Xeon W-2155 (10 Cores, 20 Threads, 3.30 GHz base, 4.50 GHz turbo, 140W TDP)
Host Memory: 128GB (4x32GB) DDR4-2666 ECC RDIMM (15-hour MemTest86 burn-in verified, 0 errors)
Accelerator: ASUS GeForce RTX 5060 Ti 16GB (Blackwell sm_120 architecture, Compute Capability 12.0)
Power Limiter: Hardware-throttled at 160W via nvidia-smi -pl 160 (15A residential circuit defense)
Thermal Interface: Honeywell PTM7950 phase-change material (anti-pump-out)
High-Throughput Storage: Silicon Power 2TB US75 PCIe Gen4 NVMe mounted on dedicated PCIe x16 slot via EZDIY-FAB heatsink adapter
Host Mount: Bare physical partition direct pass-through (wsl --mount \\.\PHYSICALDRIVE1 --bare -> /mnt/data ext4)

Critical Architecture: Defeating Memory Fragmentation & OOM

Standard Python runtimes using glibc malloc retain allocated heaps, causing dirty page accumulation and triggering Linux kernel OOM Killer (Exit 137). This engine injects libjemalloc2 combined with Polars streaming execution to guarantee deterministic deallocation.

1. Jemalloc Purging Injection

export LD_PRELOAD="/usr/lib/x86_64-linux-gnu/libjemalloc.so.2:/usr/lib/wsl/lib/libcuda.so.1"
export MALLOC_CONF="background_thread:true,dirty_decay_ms:2000,muzzy_decay_ms:2000"

Dirty and muzzy memory pages decay back to the OS within 2,000 milliseconds.

2. Disk Streaming via Polars

import polars as pl

# O(1) Constant memory sink
def stream_batch_sink(lazy_df: pl.LazyFrame, output_path: str):
    lazy_df.sink_parquet(
        output_path,
        compression="zstd",
        maintain_order=False,
        row_group_size=100_000,
        engine="streaming"
    )

3. Crash-Resilient Persistence (SQLite WAL 2PC)

PRAGMA journal_mode=WAL;
PRAGMA synchronous=NORMAL;
PRAGMA busy_timeout=10000;
PRAGMA journal_size_limit=67108864;
PRAGMA wal_autocheckpoint=10000;

Transactions commit every 50,000 records. Validated against unannounced kill -9 processes with zero database corruption.

Production Deployment: Zero-Network Isolation

To process proprietary records, patient data, and enterprise IP without GDPR or HIPAA liability, the runtime operates strictly with network capabilities severed.

docker run -d \
  --name airgapped-inference-node \
  --gpus all \
  --user $(id -u):$(id -g) \
  --network none \
  --memory="90g" \
  --memory-swap="90g" \
  --ipc=host \
  --ulimit nofile=1048576:1048576 \
  --tmpfs /tmp:rw,exec,nosuid,size=20g \
  -v /etc/passwd:/etc/passwd:ro \
  -v /etc/group:/etc/group:ro \
  -v /mnt/data/inference_jobs:/workspace/data:rw \
  -v /usr/lib/wsl/lib:/usr/lib/wsl/lib:ro \
  -e LD_PRELOAD="/usr/lib/x86_64-linux-gnu/libjemalloc.so.2:/usr/lib/wsl/lib/libcuda.so.1" \
  -e MALLOC_CONF="background_thread:true,dirty_decay_ms:2000,muzzy_decay_ms:2000" \
  -e ZMQ_MAX_SOCKETS=65535 \
  -e MAX_ZMQ_SOCKETS=65535 \
  matsubara-hpc/airgapped-engine:latest

Enterprise Implementation & Engagements

Matsubara Longevity Science Research Institute does not operate third-party data custody BPO services. We deliver tested, production-grade Air-Gapped Infrastructure as Code (IaC) and containerized pipeline runtimes directly into client infrastructure.

Option 1: Commercial Air-Gapped Docker IaC Bundle ($1,200 USD)

Instant access to production-tested infrastructure code for self-hosted deployment:

Hardened Dockerfile (nvcr.io/nvidia/pytorch:25.02-py3 / Blackwell sm_120 ready) with --network none physical network isolation.
Pre-configured libjemalloc2 runtime injection (dirty_decay_ms:2000,muzzy_decay_ms:2000) preventing glibc memory fragmentation.
Polars streaming disk-sink templates (sink_parquet two-phase atomic move) and SQLite WAL state machines (busy_timeout=10000) with SHA-256 hash chain verification.

Artifact Integrity & Verification:

Filename: airgapped-hpc-docker-iac-bundle-v1.0.0.zip
Canonical SHA-256: 1CB70C60C14C83CDD0AE799567D5CAFCF0E103B36CA7A3C29C775837689BB2FB
Terms: Provided strictly "AS IS" under UCC Section 2-316. Liability capped at purchase price ($1,200.00 USD). All sales final upon digital delivery.

Buy & Download IaC Bundle ($1,200 USD)

Option 2: Custom Private Deployment ($1,000 - $5,000 USD Fixed-Price)

We adapt and deploy the deterministic pipeline into your private cloud boundary under a strictly asynchronous, 100% written-only engagement.

Full row-count parity verification and SHA-256 integrity logs.
Milestone-based escrow contract via Upwork.

Order on Upwork Project Catalog ($1,000 - $5,000)

Official B2B Architecture LP: shotamatsubara.com
Primary Repository: GitHub: Matsubara-CEO

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