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SpaceInferX

Space-Analog AI Inference Characterization

Research project studying LLM inference and KV cache behavior under space-like operating conditions.

Research Question

How do LLM inference metrics — throughput, latency, KV cache hit rate, output correctness — degrade when compute operates under space-analog constraints: radiation-elevated BER, passive thermal management only, and intermittent network links?

Funding

$5,000 research grant — TCP networking and space-analog compute study.

Two Tracks

Track 1 — Networking (Software, active)

Characterize TCP behavior under space-analog link conditions using Python-based link emulation. Uses tc/netem for link degradation modeling.

Track 2 — Hardware (Design phase)

Modular compute unit with passive cooling, radiation-component selection, thermal interface design. Physical platform for Track 1 experiments.

Project Structure

src/
  emulation/      # Space-analog link and hardware condition emulation
  inference/      # LLM inference benchmarking (vLLM, MLC-LLM)
  kvcache/        # KV cache behavior under fault conditions
  networking/     # TCP characterization under degraded links
  thermal/        # Thermal simulation and throttling models
experiments/
  tcp_characterization/   # TCP failure modes under space-analog links
  inference_bench/        # Inference throughput/latency under faults
  kvcache_bench/          # KV cache hit rate, eviction, corruption
  thermal_sim/            # Passive cooling thermal dynamics
results/
  baseline/       # Standard datacenter conditions
  space_analog/   # Space-like conditions
  degraded/       # Intermediate degradation levels

Key Papers (from advisors and collaborators)

Paper Relevance
PagedAttention (Kwon et al., 2023) KV cache paged memory — radiation fault isolation
DCTCP (Alizadeh et al., 2010) TCP baseline for datacenter links
FlashAttention (Dao et al., 2022) Attention tiling on constrained memory hierarchy
AWQ (Lin et al., 2024) Quantization under bandwidth-constrained hardware
ShadowKV (Sun et al., 2024) KV cache offload under memory constraints
Message Ferries (Zhao et al., 2004) Intermittent connectivity networking
Snoop Protocol (Balakrishnan et al., 1995) Link-layer TCP shielding for unreliable links
L4S (Briscoe et al., 2023) Scalable congestion signaling for low-latency links

Success Metrics

  • TCP throughput degradation curve vs BER (0 to 10^-3)
  • Inference throughput (tokens/sec) vs thermal throttle level
  • KV cache hit rate vs DRAM bit error rate
  • Output faithfulness (ROUGE/perplexity) vs radiation level
  • Latency P50/P95/P99 across all conditions

Target Venues

  • SIGCOMM, NSDI (networking track)
  • MLSys, OSDI (inference systems track)
  • Hot Topics in Space Networking (if applicable)

About

Space-analog AI inference characterization: LLM serving and KV-cache behavior under radiation-elevated BER, passive thermal limits, and intermittent TCP.

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