pepperu96
- 12 skills
- 0 followers
- 6 hours ago last updated
- ▌ Cute Dsl Ref · pepperu96 bundleCuTe Python DSL API reference and implementation patterns for NVIDIA GPU kernel programming. Provides execution model, core API table, key constraints, common patterns, and documentation index. Use when: (1) writing or modifying CuTe DSL kernel code, (2) looking up CuTe DSL API syntax, (3) implementing attention/GEMM/MLA patterns in CuTe DSL, (4) understanding CuTe DSL execution model and compilation pipeline, (5) checking what CuTe DSL can and cannot do.
- ▌ Mla Analysis · pepperu96MLA (Multi-Latent Attention) cost models, regime analysis, and kernel selection guide. Use when: (1) reasoning about which kernel approach to use for a given regime, (2) understanding cost model tradeoffs between FlashMLA, FlashAttention, and MLAvar6+, (3) analyzing roofline behavior across decode/speculative/prefill regimes, (4) setting optimization targets, (5) understanding MLA math and absorption trick.
- ▌ Design Kernel · pepperu96 bundleShared kernel design workflow across all supported languages and DSLs. Provides language selection table, naming conventions, versioning rules, KernelPlan structure, composition patterns, clone workflow, implementation workflow, devlog template, and designer output contract. Use when: (1) choosing which language-specific kernel design skill to load, (2) the intended implementation language is not fixed yet, (3) you need naming or versioning guidance before selecting a DSL, (4) you are implementing any kernel regardless of DSL, (5) you are updating docs that refer to kernel design skills.
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- ▌ Learn Cute Dsl · pepperu96Workflow for learning CuTe Python DSL by reading, importing, profiling, and extracting reusable patterns from CUTLASS Blackwell example kernels. Use when: (1) studying CUTLASS CuTe DSL reference implementations, (2) importing CUTLASS examples into the project runtime infrastructure, (3) building CuTe DSL knowledge base entries from profiling experiments, (4) understanding CuTe DSL API patterns, TMA pipelining, warpgroup scheduling, or persistent kernel structure.
- ▌ Profile Kernel · pepperu96 bundleGPU kernel profiling workflow across supported kernel implementation languages. Provides commands for all 4 profiling modes (annotation, event, ncu, nsys), metric interpretation tables, bottleneck identification rules, and the output contract for returning compact results to the orchestrator. Use when: (1) profiling a kernel version, (2) interpreting profiling artifacts/reports, (3) comparing kernel versions, (4) identifying bottlenecks and optimization opportunities, (5) documenting performance in the development log.
- ▌ Optimization Catalog · pepperu96Compatibility router for the shared optimization knowledge base and the language-specific optimization catalog skills. Use when: (1) selecting which optimization catalog skill to load, (2) the implementation language is not fixed yet, (3) a workflow still references the legacy optimization-catalog skill name, (4) deciding whether a finding is shared or language-specific, (5) updating the generalized knowledge-base structure.
- ▌ Design Cute Dsl Kernel · pepperu96CuTe Python DSL kernel workflow, CuteKernel runtime wrapper, suitability gate, tiling guidance, and CuTe-specific pitfalls. Use when: (1) planning or implementing a kernel in the CuTe Python DSL, (2) the optimization needs more explicit control than cuTile exposes but should remain in a Python-driven workflow, (3) defining package naming for cute-dsl kernels, (4) documenting CuTe Python DSL design choices, (5) recording language-specific knowledge for CuTe Python DSL.
- ▌ Orchestration Workflow · pepperu96Full optimization workflow, sub-agent launch templates, agent communication contracts, default configurations, tuning strategy, and knowledge base update protocol. Use when: (1) starting an optimization cycle, (2) launching a Profiler or Designer sub-agent, (3) interpreting or formatting agent communication, (4) updating the knowledge base after a profiling or implementation iteration, (5) deciding default configurations or tuning strategy for a kernel.
- ▌ Design Cutile Dsl Kernel · pepperu96cuTile Python DSL kernel implementation patterns, CtKernel runtime wrapper, suitability gate, and cuTile-specific pitfalls. Use when: (1) creating or modifying a cuTile Python DSL kernel version, (2) implementing an optimization that still fits within cuTile's exposed control surface, (3) deciding whether cuTile is still the right DSL, (4) reviewing cuTile-specific runtime patterns. Always also load /design-kernel for shared naming, versioning, and workflow.
- ▌ Optimization Catalog Cute Dsl · pepperu96Shared optimization guidance plus CuTe Python DSL overlays. Use when: (1) selecting optimizations for a CuTe Python DSL kernel, (2) deciding whether a finding is shared or cute-dsl-specific, (3) recording CuTe Python DSL implementation notes, (4) reviewing the knowledge layout for cute-dsl work, (5) mapping shared patterns to a CuTe Python DSL implementation surface.
- ▌ Optimization Catalog Cutile Dsl · pepperu96Shared optimization guidance plus cuTile Python DSL-specific overlays. Use when: (1) selecting optimizations for a cuTile Python DSL kernel, (2) checking cuTile-specific implementation traps, (3) deciding whether a profiling finding belongs in shared knowledge or a cuTile overlay, (4) updating cuTile Python DSL optimization docs, (5) reviewing how a shared pattern maps to cuTile.