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Found 4 Skills
OpenMP skill for shared-memory parallel programming. Use when writing parallel for loops, reductions, task parallelism, SIMD directives, GPU offloading, or profiling with Score-P/TAU. Activates on queries about OpenMP, pragma omp, schedule static dynamic, reduction, false sharing, or OMP_NUM_THREADS.
Diagnose HPC runtime and scheduler problems for materials simulations, including MPI/OpenMP/GPU layout, modules, CUDA/Kokkos hints, scratch paths, walltime, job arrays, restart strategy, scheduler portability, and resource mismatch. Use when an ALREADY-SUBMITTED job failed, ran slowly, got killed, or behaved differently on a cluster than on a workstation. To author or vet a NEW submission script before running, use slurm-job-script-generator instead.
MPI skill for distributed-memory parallel programming. Use when writing MPI_Send/Recv programs, collective operations, non-blocking communication, MPI+OpenMP hybrid, or debugging with mpirun. Activates on queries about MPI_Init, MPI_Allreduce, MPI_Isend, mpirun, MPI-IO, or MPI performance.
Recommends which rocprofiler-systems runtime profiling preset (balanced, trace-gpu, trace-hpc, sys-trace, workload-trace, etc.) to pass to `rocprof-sys-run --preset=<name>` or `rocprof-sys-sample --preset=<name>` based on the user's workload and profiling goal, and returns the ready-to-run command. Use when the user asks "which preset should I use", describes a workload (GPU kernel, MPI, OpenMP, AI/ML training, production overview) and wants profiling guidance, or invokes `rocprof-sys-run`/`rocprof-sys-sample` without picking a preset. Do NOT use for CMake build presets (`cmake --preset debug|release|ci`) used to configure/compile rocprofiler-systems itself — that is a build-configuration concern, not a profiling-run concern.