{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/7"}],"enrichment":{"capability":"FlyDSL is a Python DSL and embedded MLIR compiler for authoring high-performance GPU kernels with explicit data layouts, tiling, and partitioning on ROCm hardware.","skillfed_tags":["gpu-kernels","mlir-compiler","rocm"],"use_cases":["Author custom GPU kernels with explicit tiling and memory layout control without writing CUDA or HIP directly.","Prototype and tune high-performance matrix multiplication and tensor operations on ROCm GPUs.","Express complex data movement and swizzling patterns using layout algebra instead of manual indexing.","Build production GPU kernels (GEMM, MoE, normalization) with the included pre-built kernel library.","Benchmark and profile kernel performance using the built-in autotune and benchmarking infrastructure."],"what_it_does":"FlyDSL is a Python domain-specific language for writing GPU kernels that run on ROCm hardware. It sits atop an embedded MLIR compiler stack (the Fly dialect) and lets you express kernel structure, data layouts, tiling strategies, and memory movement at a high level in Python, then compile them down to GPU machine code. The package bundles MLIR Python bindings so you don't need a separate MLIR installation.\n\nThe core abstraction is a layout system\u2014Shape, Stride, and Layout objects that map logical coordinates to physical memory indices. You compose these layouts using algebra operations (composition, product, partition) to express complex data access patterns like swizzling, tiling, and vectorization. You decorate Python functions with `@flyc.kernel` or `@flyc.jit`, write kernel logic using FlyDSL's expression API (arithmetic, vector, GPU, ROCDL, buffer, math, and memory operations), and the JIT compiler handles lowering to GPU code. Pre-built kernels for GEMM, MoE, Softmax, and Norm are included.","worth_installing":"Yes, if you are developing GPU kernels for ROCm hardware and want to express layouts and tiling at a high level. The package is actively maintained, has no known vulnerabilities, and bundles MLIR so setup is simpler than standalone MLIR. Install friction is medium due to ROCm dependency and optional source builds, but pre-built wheels for Python 3.10\u20133.14 are available. Not suitable if you need CUDA, OpenCL, or non-ROCm GPU support."},"id":"flydsl","links":{"html":"https://skillfed.io/packages/flydsl","md":"https://skillfed.io/packages/flydsl.md","pypi":"https://pypi.org/project/flydsl/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-09","license_spdx":null,"license_treatment":"permissive","name":"flydsl","python_support":"supports_current","summary":"FlyDSL - ROCm Domain Specific Language for layout algebra (Python + embedded MLIR runtime)"},"popularity":{"monthly_downloads":107165,"position":12627,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.3.1"}