Expert integration with NVIDIA GPU-accelerated math libraries. Configure cuBLAS tensor core operations, generate cuBLAS GEMM calls, integrate cuDNN layers, handle algorithm selection, and support mixed-precision operations.
Expert skill for GPU debugging using CUDA-GDB and NVIDIA Compute Sanitizer. Detect memory errors, race conditions, uninitialized memory access, validate atomic operations, analyze kernel synchronization issues, and generate debugging reports with recommendations.
Expert skill for CUDA Graph capture and optimization for reduced launch overhead. Capture CUDA operations into graphs, instantiate and execute graph instances, update graph node parameters, profile graph vs stream execution, design graph-friendly kernel patterns, and optimize launch latency for inference.
Deep integration with NVIDIA CUDA toolkit for kernel development, compilation, and debugging. Execute nvcc compilation with optimization flags analysis, generate and validate CUDA kernel code, analyze PTX/SASS assembly output, and configure execution parameters.
High-performance kernel template libraries and DSLs. Generate CUTLASS GEMM configurations, implement Triton kernel definitions, configure epilogue operations, tune tile sizes and warp arrangements, and benchmark against cuBLAS.
Expert skill for automated GPU performance benchmarking and regression detection. Design micro-benchmarks, measure kernel execution time with CUDA events, calculate achieved vs theoretical performance, generate comparison reports, detect regressions in CI/CD, and profile power/thermal characteristics.
Specialized skill for GPU memory hierarchy analysis and optimization. Analyze memory access patterns, detect bank conflicts, optimize cache utilization, profile global memory bandwidth, and generate optimized memory access code patterns.
AMD HIP and ROCm ecosystem for cross-platform GPU development. Execute hipify conversion tools, generate HIP-compatible kernel code, handle CUDA/HIP API differences, configure ROCm toolchain, and profile with rocprof.