trainium

Training Object Permanence in World Models — the codebase

Foundation model benchmarking tool. Run any model on any AWS platform and benchmark for performance across instance type and serving stack options.

Community maintained hardware plugin for vLLM on AWS Neuron

AI/ML and HPC at planetary scale. One API. Every Accelerator. Any Region. MIT-0 licensed

Predict AWS Trainium val_bpb before spending chip hours: a calibrated simulator + GPU proxy from the Trainium Frontier challenge

vLLM Omni backend plugin for diffusion and multimodal generation on AWS Trainium

Production LLM pipeline on AWS Trainium and Inferentia: LoRA fine-tune Llama 3.1 8B on a trn1.2xlarge, ship the adapter through S3, serve it with vLLM on an inf2.xlarge, and measure everything (TTFT/TPOT percentiles, tokens/s, MFU, goodput at SLO) with compile costs included and failures recorded as receipts.

A hybrid testbed for evaluating top open-source LLMs (like gpt-oss-20b and Llama 3.3) on local, cloud GPUs, and AWS Inferentia2/Trainium instances, focusing on vLLM optimization, capacity management, kernel bypass, hardware-software co-design, as well as supporting infrastructure such as NCCL, RDMA, NVMeoF.

AWS TorchNeuron Deep Learning Projects using Trainium1 Instances

Open-source calculator for AI accelerator compatibility across TPUs, Trainium/Inferentia, Gaudi, and NVIDIA GPUs

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.