Showing 1178 open source projects for "linux cpu"

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  • 1
    Zenith

    Zenith

    Sort of like top or htop but with zoom-able charts, CPU, GPU

    In terminal graphical metrics for your *nix system written in Rust. The make file provides for building fully static versions on Linux against the musl C library. It requires musl-gcc to be installed on the system. Install "musl-tools" package on debian/ubuntu derivatives, "musl-gcc" on fedora and equivalent on other distributions from their standard repos. If one needs to build with NVIDIA support in a virtual environment, then it requires some more setup since typically the VM software...
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  • 2
    FastChat

    FastChat

    Open platform for training, serving, and evaluating language models

    ... to commands above to offload weights that don't fit on your GPU onto the CPU memory. This requires 8-bit compression to be enabled and the bitsandbytes package to be installed, which is only available on linux operating systems.
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  • 3
    Amazon CodeGuru Profiler Python Agent

    Amazon CodeGuru Profiler Python Agent

    Amazon CodeGuru Profiler Python Agent

    Amazon CodeGuru Profiler collects runtime performance data from your live applications and provides recommendations that can help you fine-tune your application performance. Using machine learning algorithms, CodeGuru Profiler can help you find your most expensive lines of code and suggest ways you can improve efficiency and remove CPU bottlenecks. CodeGuru Profiler provides different visualizations of profiling data to help you identify what code is running on the CPU, see how much time...
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  • 4
    Simd Library

    Simd Library

    C++ image processing and machine learning library with using of SIMD

    ... the following CPU extensions: SSE, AVX, AVX-512, and AMX for x86/x64, and NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows and Linux, MSVS, G++ and Clang compilers, MSVS projects, and CMake build systems.
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  • 5
    llama2-webui

    llama2-webui

    Run any Llama 2 locally with gradio UI on GPU or CPU from anywhere

    Running Llama 2 with gradio web UI on GPU or CPU from anywhere (Linux/Windows/Mac).
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  • 6
    parca

    parca

    Continuous profiling for analysis of CPU and memory usage

    Continuous profiling for analysis of CPU, memory usage over time, and down-to-the-line number. Saving infrastructure costs, improving performance, and increasing reliability. A single profiler, using eBPF, automatically discovers targets from Kubernetes or systemd across the entire infrastructure with very low overhead. Supports C, C++, Rust, Go, and more. Both producing pprof formatted profiles with the eBPF-based profiler and ingesting any pprof formatted profiles allowing for wide language...
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  • 7
    Logagent

    Logagent

    Extensible log shipper with input/output plugins, buffering, etc.

    Logagent is a modern, open-source, lightweight log shipper. It is like Filebeat and Logstash in one, without the JVM memory footprint. It comes with out-of-the-box and extensible log parsing, on-disk buffering, secure transport, and bulk indexing to Elasticsearch, Sematext Logs, and other destinations. Its low memory footprint and low CPU overhead make it suitable for deploying on edge nodes and devices, while its ability to parse and structure logs makes it a great Logstash alternative.
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  • 8
    Thread Affinity

    Thread Affinity

    Bind a java thread to a given core

    Lets you bind a thread to a given core, this can improve performance (this library works best on linux). Java-Thread-Affinity will try to use JNA to provide access to native thread-handling functions. JNA should be installed on your system to get the most from this library. Java-Thread-Affinity currently depends on JNA version 4.4.0, which in turn depends on a version of GLIBC >= 2.14. If your operating system is an old one, with a version of GLIBC released before 2011, this library...
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  • 9
    Likwid

    Likwid

    Performance monitoring and benchmarking suite

    Likwid is a simple to install and use toolsuite of command line applications and a library for performance oriented programmers. It works for Intel, AMD, ARMv8 and POWER9 processors on the Linux operating system. There is additional support for Nvidia and AMD GPUs. There is support for ARMv7 and POWER8/9 but there is currently no test machine in our hands to test them properly.
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  • 10
    Ultralight

    Ultralight

    Lightweight, high-performance HTML renderer for game developers

    Use our portable, WebKit-based SDK to effortlessly display modern web content everywhere. Available for desktop apps, game consoles, TVs, embedded device displays, servers, and more. Official API for C and C++, with bindings for more. Render web-content on the GPU via Direct3D, Metal, OpenGL, or your own engine for unmatched visual performance. Render web-content on the CPU via SIMD/parallel for incredibly easy integration with any environment (including server-side!). Ultralight is engineered...
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  • 11
    Coffee GB

    Coffee GB

    Gameboy emulator in Java 8

    Coffee GB is a Gameboy Color emulator written in Java 8. It's meant to be a development exercise. More info can be found in the blog post. First I implemented all the Gameboy CPU opcodes. It’s not exactly the Z80, but it’s pretty close. As a reference, I’ve used the GameBoy CPU Manual - later on I discovered that it has a few typos and is not specific enough for some of the operations. After implementing the opcodes and memory (modelled by an int[] array) I was eager to check whether it’s...
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  • 12
    PyTorch/XLA

    PyTorch/XLA

    Enabling PyTorch on Google TPU

    PyTorch/XLA is a Python package that uses the XLA deep learning compiler to connect the PyTorch deep learning framework and Cloud TPUs. You can try it right now, for free, on a single Cloud TPU with Google Colab, and use it in production and on Cloud TPU Pods with Google Cloud. Take a look at one of our Colab notebooks to quickly try different PyTorch networks running on Cloud TPUs and learn how to use Cloud TPUs as PyTorch devices. We are also introducing new TPU VMs for more transparent...
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  • 13
    DALI

    DALI

    A GPU-accelerated library containing highly optimized building blocks

    ..., cropping, resizing, and many other augmentations. These data processing pipelines, which are currently executed on the CPU, have become a bottleneck, limiting the performance and scalability of training and inference. DALI addresses the problem of the CPU bottleneck by offloading data preprocessing to the GPU. Additionally, DALI relies on its own execution engine, built to maximize the throughput of the input pipeline.
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  • 14
    Scalene

    Scalene

    High-performance CPU, GPU, and memory profiler for Python

    Scalene is a high-performance CPU, GPU and memory profiler for Python that does a number of things that other Python profilers do not and cannot do. It runs orders of magnitude faster than other profilers while delivering far more detailed information. Once Scalene has profiled your program, it will launch a web browser with an interactive user interface (all processing is done locally). Hover over bars to see breakdowns of CPU and memory consumption, and click on underlined column headers...
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  • 15
    gops

    gops

    A tool to list and diagnose Go processes currently running

    ... the target binary as the same user that runs gops binary. To use gops in a remote mode you need to know target's agent address. In Local mode use process's PID as a target; in Remote mode target is a host:port combination. gops supports CPU and heap pprof profiles. After reading either heap or CPU profile, it shells out to the go tool pprof and let you interactively examine the profiles.
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  • 16
    TensorLy

    TensorLy

    Tensor Learning in Python

    TensorLy is a Python library that aims at making tensor learning simple and accessible. It allows to easily perform tensor decomposition, tensor learning and tensor algebra. Its backend system allows to seamlessly perform computation with NumPy, PyTorch, JAX, TensorFlow, CuPy or Paddle, and run methods at scale on CPU or GPU.
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  • 17
    MegEngine

    MegEngine

    Easy-to-use deep learning framework with 3 key features

    .... Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference.
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  • 18
    PRoot

    PRoot

    Chroot, mount --bind, and binfmt_misc without privilege/setup

    PRoot is a user-space implementation of chroot, mount --bind, and binfmt_misc. This means that users don't need any privileges or setup to do things like using an arbitrary directory as the new root filesystem, making files accessible somewhere else in the filesystem hierarchy, or executing programs built for another CPU architecture transparently through QEMU user mode. Also, developers can use PRoot as a generic Linux process instrumentation engine thanks to its extension mechanism, see CARE...
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  • 19
    CppServer

    CppServer

    Fast and low latency asynchronous socket server & client C++ library

    Ultra-fast and low latency asynchronous socket server & client C++ library with support TCP, SSL, UDP, HTTP, HTTPS, WebSocket protocols, and 10K connections problem solution. Cross platform (Linux, MacOS, Windows) Asynchronous communication. Supported CPU scalability designs: IO service per thread, thread pool. Supported transport protocols: TCP, SSL, UDP, UDP multicast. Supported Web protocols: HTTP, HTTPS, WebSocket, WebSocket secure. Supported Swagger OpenAPI iterative documentation...
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  • 20
    frugally-deep

    frugally-deep

    A lightweight header-only library for using Keras (TensorFlow) models

    Use Keras models in C++ with ease. A lightweight header-only library for using Keras (TensorFlow) models in C++. Works out-of-the-box also when compiled into a 32-bit executable. (Of course, 64 bit is fine too.) Avoids temporarily allocating (potentially large chunks of) additional RAM during convolutions (by not materializing the im2col input matrix). Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can run...
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  • 21
    ImplicitGlobalGrid.jl

    ImplicitGlobalGrid.jl

    Distributed parallelization of stencil-based GPU and CPU applications

    ImplicitGlobalGrid is an outcome of a collaboration of the Swiss National Supercomputing Centre, ETH Zurich (Dr. Samuel Omlin) with Stanford University (Dr. Ludovic Räss) and the Swiss Geocomputing Centre (Prof. Yuri Podladchikov). It renders the distributed parallelization of stencil-based GPU and CPU applications on a regular staggered grid almost trivial and enables close to ideal weak scaling of real-world applications on thousands of GPUs [1, 2, 3]. ImplicitGlobalGrid relies on the Julia...
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  • 22
    Mosec

    Mosec

    A high-performance ML model serving framework, offers dynamic batching

    Mosec is a high-performance and flexible model-serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API.
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  • 23
    Chinese-LLaMA-Alpaca-2 v2.0

    Chinese-LLaMA-Alpaca-2 v2.0

    Chinese LLaMA & Alpaca large language model + local CPU/GPU training

    This project has open-sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA , these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which...
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  • 24
    NVIDIA Merlin

    NVIDIA Merlin

    Library providing end-to-end GPU-accelerated recommender systems

    ... on the NVIDIA developer website. Transform data (ETL) for preprocessing and engineering features. Accelerate your existing training pipelines in TensorFlow, PyTorch, or FastAI by leveraging optimized, custom-built data loaders. Scale large deep learning recommender models by distributing large embedding tables that exceed available GPU and CPU memory. Deploy data transformations and trained models to production with only a few lines of code.
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  • 25
    dperf

    dperf

    DPDK based 100Gbps network performance and load testing software

    ... of network package processing capability for NIC and CPU. Can be used as a high-performance HTTP server or client for load testing.
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