Popular GitHub Repositories for Cpus

Sparsity-aware deep learning inference runtime for CPUs

The Compute Library is a set of computer vision and machine learning functions optimised for both Arm CPUs and GPUs using SIMD technologies.

Acceleration package for neural networks on multi-core CPUs

World's fastest ANPR / ALPR implementation for CPUs, GPUs, VPUs and NPUs using deep learning (Tensorflow, Tensorflow lite, TensorRT, OpenVX, OpenVINO). Multi-Charset (Latin, Korean, Chinese) & Multi-OS (Jetson, Android, Raspberry Pi, Linux, Windows) & Multi-Arch (ARM, x86).

Transforms your CasADi functions into batchable JAX-compatible functions. By combining the power of CasADi with the flexibility of JAX, JAXADi enables the creation of efficient code that runs smoothly on CPUs, GPUs, and TPUs.

Workflow that shows how to train neural networks on EC2 instances with GPU support and compares training times to CPUs

A Really Scalable RL Framework to 10k+ CPUs

AML's goal is to make benchmarking of various AI architectures on Ampere CPUs a pleasurable experience :)

This repository demonstrates LLM execution on CPUs using packages like llamafile, emphasizing low-latency, high-throughput, and cost-effective benefits for inference and serving.

? Olosh — Make the Idle CPUs Work

eLLM provides million-token inference on CPUs

The project was undertaken as part of the Intel Unnati Industrial Training program for the year 2024. The primary objective of this project aligns with Problem Statement PS-04: Introduction to GenAI LLM Inference on CPUs and subsequent LLM Model Finetuning for the development of a Custom Chatbot.

A guide on how to run LLMs on intel CPUs

Neural Network C is an advanced neural network implementation in pure C, optimized for high performance on CPUs and NVIDIA GPUs.

In this work, we focus on proposing a theoretically grounded set of methods to enable users with limited computational resources to generate their own LoRAs based on a bank of dataset and adapters with similar configs utilizing standard laptops equipped only with Central Processing Units (CPUs).

measuring the difference in performance between CPUs and GPUs when processing a user prompt locally on a machine