Google has introduced HEIR (Homomorphic Encryption Intermediate Representation), an open-source compiler toolchain that enables pre-trained AI models to operate on encrypted data, aiming to make homom…
OpenAI is hiring a Software Engineer, Trainium in San Francisco with a salary range of $295k–380k/yr, to build and optimize its inference stack for AWS Trainium, developing high-performance kernels an…
Google released HEIR (Homomorphic Encryption Intermediate Representation), an open-source compiler that converts pre-trained AI models to run on fully encrypted data, on August 14, 2026. The tool, bui…
Xanadu's quantum compiler Catalyst, built for the PennyLane library, accidentally became an LLVM compiler for JAX when users fed it pure JAX NumPy code without quantum instructions, bypassing XLA to l…
XLA, the compiler behind JAX, TensorFlow, and PyTorch/XLA, optimizes array programs by freezing shapes, statically allocating buffers, and fusing operations against a global cost model, which makes it…
XLA, the compiler under JAX, TensorFlow, and PyTorch/XLA, uses two intermediate representations: classic HLO (a hand-built C++ IR) and MLIR dialects such as StableHLO and CHLO, with a translation laye…
Researchers released four natural-language-to-MLIR benchmarks totaling 410 in-scope pairs and a three-layer schema-derived constraint stack that lets SmolLM2-1.7B match or exceed 15B-34B code LMs on s…
A new MLIR-based compilation method for large language models, developed by researchers and implemented in the TPU-MLIR compiler and LLM-TPU deployment project, addresses challenges in importing train…
Triton is a compiler with a Python frontend that parses a function's AST, runs it through an MLIR pipeline, and emits a GPU binary, never executing the Python function as Python. The compiler handles …
Researchers seeking endorsement for arXiv submission of their manuscript "Nova: An End-to-End MLIR Compiler for Deep Learning" request an established researcher to review and endorse their work in cat…
Chris Lattner created MLIR (Multi-Level Intermediate Representation) in 2018 at Google to solve the problem of fragmented compiler infrastructure across different hardware targets and programming mode…
Researchers have published a paper arguing that the design principles underlying MLIR, a compiler infrastructure for AI models, have formal theoretical correspondences that can clarify abstraction com…
MLIR, a compiler infrastructure framework, has become the foundation for numerous machine learning compilers including XLA, Triton, Mojo, Torch-MLIR, IREE, and ONNX-MLIR. It provides a reusable IR con…
Google launched Coral, a full-stack platform for edge AI that combines an AI-first hardware architecture with a unified developer experience to enable efficient, local AI processing. The platform prov…
Researchers have developed CPPL, a compiler-mediated hardware design framework that converts large language model-assisted circuit generation into a statically checkable frontend problem. The system c…