{"id":29416214,"url":"https://github.com/tensoriumcore/tensorium-simd2gpu","last_synced_at":"2025-07-11T19:02:09.729Z","repository":{"id":301052236,"uuid":"1008016260","full_name":"TensoriumCore/Tensorium-simd2gpu","owner":"TensoriumCore","description":"A compiler module that lifts SIMD intrinsics (e.g. AVX) into architecture-independent MLIR representations, enabling automatic transformation and execution on GPU targets.","archived":false,"fork":false,"pushed_at":"2025-07-03T16:25:20.000Z","size":34,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-07-03T17:35:13.593Z","etag":null,"topics":["compiler","compiler-plugin","llvm","mlir","mlir-dialect","numerical-relativity","tensorium"],"latest_commit_sha":null,"homepage":"","language":"MLIR","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/TensoriumCore.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-24T22:30:52.000Z","updated_at":"2025-07-03T16:25:25.000Z","dependencies_parsed_at":"2025-06-24T23:40:24.014Z","dependency_job_id":null,"html_url":"https://github.com/TensoriumCore/Tensorium-simd2gpu","commit_stats":null,"previous_names":["tensoriumcore/tensorium-simd2gpu"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/TensoriumCore/Tensorium-simd2gpu","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TensoriumCore%2FTensorium-simd2gpu","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TensoriumCore%2FTensorium-simd2gpu/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TensoriumCore%2FTensorium-simd2gpu/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TensoriumCore%2FTensorium-simd2gpu/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TensoriumCore","download_url":"https://codeload.github.com/TensoriumCore/Tensorium-simd2gpu/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TensoriumCore%2FTensorium-simd2gpu/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264878580,"owners_count":23677450,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["compiler","compiler-plugin","llvm","mlir","mlir-dialect","numerical-relativity","tensorium"],"created_at":"2025-07-11T19:02:08.619Z","updated_at":"2025-07-11T19:02:09.605Z","avatar_url":"https://github.com/TensoriumCore.png","language":"MLIR","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# Tensorium SIMD2GPU\n\n**Tensorium SIMD2GPU** is a compiler module designed to lift SIMD intrinsics (such as AVX) into architecture-independent MLIR representations. It enables automatic transformation of vectorized CPU code into GPU-executable kernels through MLIR lowering pipelines.\n\nThis component is part of the [Tensorium Foundation](https://github.com/TensoriumCore), whose goal is to simplify and accelerate tensor-based computations in numerical physics, with a focus on general relativity.\n\n## Features\n- Translation of AVX (and potentially SSE/NEON) intrinsics into MLIR `vector` and `memref` operations\n- Intermediate representation suitable for targeting GPU backends (CUDA, Metal)\n- Integration with Clang plugins via `#pragma tensorium target(gpu)`\n- Support for JIT compilation and execution using MLIR's `ExecutionEngine`\n\n## Status\n\nThis module is currently under active development. The initial focus is on:\n- Identifying and translating SSE/AVX2/AVX512 intrinsics from LLVM IR\n- Emitting MLIR dialects (`vector`, `gpu`, `memref`)\n- Building a lightweight infrastructure for runtime GPU execution\n\n## License\n\nMIT License\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensoriumcore%2Ftensorium-simd2gpu","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftensoriumcore%2Ftensorium-simd2gpu","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensoriumcore%2Ftensorium-simd2gpu/lists"}