SV Advanced Computing, LLC
Independent research and consulting in HPC performance optimization, GPU computing, and AI infrastructure. We profile, analyze, and optimize at the intersection of hardware and software.
A structured practice repository exploring two ways to run multiple Claude agents in parallel — Zed's native thread system and the Claude API's async Python SDK. The repo is published; a follow-up post will walk through the code live.
Documenting the profiling methodology and toolchain we'll use across our AI framework performance investigations. Covers Nsight Systems, Nsight Compute, PyTorch profiler integration, and custom instrumentation approaches.
Profiling and optimization of PyTorch, NeMo, Megatron-Core, and inference runtimes (vLLM, TRT-LLM). End-to-end training and serving pipeline analysis.
Deep performance characterization on NVIDIA and AMD GPU architectures. Memory hierarchy analysis, occupancy tuning, kernel optimization using Nsight and ROCm profiling tools.
MPI, NCCL/RCCL communication optimization. Multi-node scaling analysis. Performance engineering for exascale-class systems.
Beyond vendor tools — custom profiling, roofline modeling, memory bandwidth characterization, and performance modeling for novel workloads.