Stars
Fast, flexible, elastically deterministic data loading for foundation model training
Project Tapestry aims to give every nation and participant frontier AI they can call their own — uniting a global consortium to train a shared frontier model family from which partners build and ow…
OpenTela is a decentralized compute fabric for running machine learning applications.
A Rust framework for correct and performant distributed systems
AI model training on heterogeneous, geo-distributed resources
Redset is a dataset containing three months worth of user query metadata that ran on a selected sample of instances in the Amazon Redshift fleet. We provide query metadata for 200 provisioned and s…
CUDA benchmarks for measuring GPU utilization and interference
A lightweight, user-friendly data-plane for LLM training.
Lightweight Helm IDE written in Rust with the Tauri framework... it also uses HTMX btw
Load generator and trace sampler for serverless computing
An interference-aware scheduler for fine-grained GPU sharing
Modyn is a research-platform for training ML models on growing datasets.
eth-easl / cachew
Forked from tensorflow/tensorflowML Input Data Processing as a Service. This repository contains the source code for Cachew (built on top of TensorFlow).
DuckDB is a high-performance analytical database system
vHive: Open-source framework for serverless experimentation
SeBS: serverless benchmarking suite for automatic performance analysis of FaaS platforms.
Reference implementations of MLPerf® training benchmarks
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.