Showing 41-60 of 75 projects
Apache BookKeeper is a scalable, fault tolerant and low latency storage service optimized for append-only workloads.
This is a Verilog-based GPGPU hardware project for accelerating AI/ML workloads.
A distributed real-time machine learning platform built on Apache Spark and Kafka for large-scale workloads.
AIStore: A scalable, high-performance, and high-availability storage solution for AI applications and workloads.
A domain-specific language for expressing machine learning workloads, useful for vibe coders building with AI tools.
Kubernetes node autoscaler for dynamic workload scaling with flexibility and performance
A Python library to track and report carbon emissions from computational workloads.
A Kubernetes GitOps solution for deploying workloads from Git to large fleets of Kubernetes clusters.
A QoS-based scheduling system for optimal layout and status of workloads like microservices, AI jobs, etc.
A Python-based data infrastructure platform for declarative, incremental multimodal AI workloads.
A Mac utility to enable/disable Turbo Boost, which can help boost performance on certain workloads.
A fast, embeddable column database written in Go, optimized for AI/ML workloads.
A specification for a standard interface to expose storage capabilities to containerized workloads.
Tools for building GPU clusters for machine learning and AI workloads
OpenXuantie - OpenC910 Core is a Verilog-based hardware design for the RISC-V C910 core, targeted at AI and ML workloads.
Bitcask is a fast and durable key-value store written in Erlang, designed for high-throughput workloads.
A high-performance, scalable, and distributed workflow framework for Golang developers.
Pogreb is an embedded key-value store for read-heavy workloads, written in Go, suitable for vibe coders.
Digdag is a workload automation system that simplifies complex workflows and task scheduling.
A Rust library that facilitates running WebAssembly/WASI workloads managed by the containerd container runtime.
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