Fast diffusion-transformer inference across accelerators — AWS Trainium, TPU, and more. CLI, Python API, OpenAI-compatible server.
Custom AWS Transform agent that migrates PyTorch/Triton kernels to AWS Trainium NKI (@nki.jit) and compiles, numerically verifies, and profiles every candidate on a real Trainium device before opening a PR.
ESMC-300M native PyTorch benchmark package for AWS Trainium2.
Random number generation for AWS Trainium via NKI (cuRAND-equivalent) — Philox counter-based RNG, standard distributions, Sobol / Halton / Latin-hypercube quasi-random sequences for Monte Carlo and QMC.
FFT and complex-valued tensor operations for AWS Trainium via NKI (cuFFT-equivalent) — Cooley-Tukey, Bluestein, STFT, ComplexTensor and complex NN layers.
Production-ready multilingual customer support system using LLaMA-3, RLHF, DeepSpeed, and AWS Trainium.
Scientific computing library suite for AWS Trainium via NKI — the cuFFT/cuBLAS/cuRAND/cuSOLVER/cuSPARSE/cuTENSOR equivalents for Neuron. Python-first, PyTorch fallback everywhere, Apache-2.0.
A high-performance Python SDK for running Lattice QCD simulations on AWS Trainium and Inferentia instances.
BLAS Levels 1–3 for AWS Trainium via NKI (cuBLAS-equivalent) — GEMM with stationary-tile reuse, batched GEMM, TRSM, validated DF-MP2 for quantum chemistry.
Linear solvers and eigendecomposition for AWS Trainium via NKI (cuSOLVER-equivalent) — Jacobi eigh, Cholesky/LU/QR factorizations, CG/GMRES iterative solvers, Newton-Schulz inverse square root.
Clean-room port of NVIDIA Aerial 5G L1 to AWS Trainium via NKI. Agentic, hardware-in-the-loop. Views are the author's own.
Pseudo-spectral direct numerical simulation (DNS) of the Taylor-Green vortex on AWS Neuron: NKI kernels on Inferentia2 and Trainium1, 3-D FFTs as matmuls, all-to-all collectives inside the kernel and a libnrt C driver, in fp32 up to 512^3, checked against an fp64 oracle and Trainium1 references. Sample code for HPC and CFD engineers.
Sparse matrix operations for AWS Trainium via NKI (cuSPARSE-equivalent) — CSR/COO formats, SpMV and SpMM via gather-matmul-scatter, Schwarz integral screening for quantum chemistry.
QUDA-inspired Lattice QCD SDK for AWS Trainium and Inferentia via PyTorch/Neuron
Tensor contractions for AWS Trainium via NKI (cuTENSOR-equivalent) — einsum with contraction planning, CP/PARAFAC and Tucker decompositions, density-fitted post-Hartree-Fock patterns.
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