Master TypeScript with advanced types, generics, and strict type safety. Handles complex type systems, decorators, and enterprise-grade patterns. Use PROACTIVELY for TypeScript architecture, type inference optimization, or advanced typing patterns.
Refactor legacy codebases, migrate outdated frameworks, and implement gradual modernization. Handles technical debt, dependency updates, and backward compatibility. Use PROACTIVELY for legacy system updates, framework migrations, or technical debt reduction.
Converting PyTorch model weights to Keras h5 format for keras_cv_attention_models
Validate voxtype binaries for CPU instruction contamination. Use when checking release binaries for AVX-512 or GFNI instruction leaks that would crash on older CPUs.
This skill should be used when the user asks to "optimize TypeScript performance", "speed up tsc compilation", "configure tsconfig.json", "fix type errors", "improve async patterns", or encounters TS errors (TS2322, TS2339, "is not assignable to"). Also triggers on .ts, .tsx, .d.ts file work involving type definitions, module organization, or memory management. Does NOT cover TypeScript basics, framework-specific patterns, or testing.
Provides guidance for writing and benchmarking optimized CUDA kernels for NVIDIA GPUs (H100, A100, T4) targeting HuggingFace diffusers and transformers libraries. Supports models like LTX-Video, Stable Diffusion, LLaMA, Mistral, and Qwen. Includes integration with HuggingFace Kernels Hub (get_kernel) for loading pre-compiled kernels. Includes benchmarking scripts to compare kernel performance against baseline implementations.
Operational guide for enabling packed sequences and long-context config paths in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.
Validate and use MoE expert-parallel communication overlap in Megatron-Bridge, including overlap_moe_expert_parallel_comm, delay_wgrad_compute, and flex dispatcher backends such as DeepEP and HybridEP.
Design and implement data-flow analyses for compiler optimization
NVIDIA Collective Communications Library integration for multi-GPU operations. Initialize NCCL communicators, execute collective operations, configure communication topologies, profile collective performance, and support RCCL for AMD compatibility.
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.
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.
Cross-vendor OpenCL runtime management and kernel development. Query platforms/devices, generate portable OpenCL C kernel code, handle vendor-specific extensions, manage contexts and command queues, compile and cache programs.
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.
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.
Exploit development automation using pwntools framework
Console optimization skill for memory constraints and TCRs.
Expert skill for FPGA place and route optimization and physical implementation
Vendor IP core configuration and integration expertise for FPGA designs
Expert skill for C/C++ to RTL conversion using High-Level Synthesis tools
Expert skill for AMBA AXI protocol implementation and verification in FPGA designs
Embedded wireless protocol implementation (LoRa, Zigbee, Thread, Matter)
