A systems research project exploring how Zig changes the design of dynamic runtimes as a high-level Python implementation.
A closed-loop security runtime preventing "The Great Exfiltration" and Indirect Prompt Injection in Autonomous AI Agents.
Linux network namespace-based transport performance benchmarking framework using tc, netem, iperf3 and optional eBPF instrumentation.
Experimental Linux RFC for an HBF/CXL-era AI memory control plane: runtime hints, prefetch, placement, and tiering.
Experimental Linux kernel patchset and benchmark suite for semantic memory hints in inference workloads. Explores whether user-space intent (streaming vs reuse vs ephemeral memory) can influence reclaim behavior in Multi-Gen LRU (MGLRU).
Trace-driven research harness for KV-cache hierarchy policy evaluation in long-context LLM inference.
Runtime-core research for long-lived AI surfaces: worker ownership, transaction scheduling, and bounded projection.
Simulation study of cache architecture tradeoffs under concurrency — partitioned vs LRU vs client affinity, with trace-driven evaluation on Twitter cache workloads
Deterministic stability framework for stateful AI recovery under bounded compute with nonlinear collapse analysis.
Runtime for survivable autonomous software agents using WASM, migration, and runtime economics.
Frictionless Computing: Entropy-Based Operation Filtering for 10x-1000x Effective Speedup
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