Results for “gpu-cluster”

GPU-safe parallel processing patterns for KINTSUGI to prevent OOM crashes and ensure Jupyter-compatible progress output

GPU-accelerated correlation matrix computation with persistent SQLite caching to eliminate bottleneck at correlation calculation during symbol selection

GPU-only SLURM scheduling for KINTSUGI: never use CPU fallback — measured speedups: stitch 25x, decon 5x, EDF 15x (~13x full cycle)

CLI-team runtime for claude, codex, gemini, antigravity, grok, or cursor workers in tmux panes when you need process-based parallel execution

Detect and validate GPU availability for MATLAB GPU computing. Use when the user can't use their GPU, or is setting up or selecting a GPU. Triggers on: gpuDevice, GPU setup, check GPU, GPU not found, GPU not working, can't use GPU, GPU not available, unable to find a supported GPU device, compatible GPU, canUseGPU, validateGPU.

Clusters a GitHub issue backlog by root cause into plan-master issues, redirects children with a standardized comment, and bundles architectural-fix PRs that close clusters atomically.

Preventing Jupyter cell hangs with explicit CuPy GPU memory cleanup

Detect which HPC cluster you are on and load the correct job submission instructions. Use when the user asks to submit, run, or schedule a job, or when you need to know which cluster environment you are in.

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.