Search Results for "cpu benchmark linux"
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Showing 111 open source projects for "cpu benchmark linux"
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Benchmark
A microbenchmark support library
A library to benchmark code snippets, similar to unit tests. -
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CPU Features
A cross platform C99 library to get cpu features at runtime
cpu_features is a cross-platform C library developed by Google that provides a simple and efficient way to detect available CPU features at runtime across a wide range of architectures and operating systems. It enables applications to determine which instruction sets (such as SSE, AVX, or NEON) are supported on the host machine, allowing developers to optimize performance dynamically. The library supports numerous architectures—including x86, ARM, AArch64, MIPS, POWER, RISCV, LoongArch, and s390x—and works on major operating systems like Linux, macOS, Windows, FreeBSD, Android, and iOS. ... -
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Crow Framework
A Fast and Easy to use microframework for the web
A Fast and Easy to use microframework for the web. Crow is a C++ framework for creating HTTP or Websocket web services. It uses routing similar to Python's Flask which makes it easy to use. It is also extremely fast, beating multiple existing C++ frameworks as well as non-C++ frameworks. Crow is provided free of charge courtesy of everyone who is donating their money, time, and expertise to keep it going. The 1000-mile journey begins with a single step. Get started by installing Crow and... -
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Google Highway
Performance-portable, length-agnostic SIMD with runtime dispatch
Google Highway is a high-performance C++ library designed to provide portable SIMD (Single Instruction, Multiple Data) vectorization across multiple CPU architectures while maintaining predictable and efficient behavior. It abstracts low-level vector intrinsics into a consistent API that maps closely to hardware instructions, allowing developers to write high-performance code without relying heavily on compiler auto-vectorization. Highway enables the same source code to run across different... -
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HLSL++
Math library using HLSL syntax with multiplatform SIMD support
HLSL++ is a header-only C++ math library designed to replicate the syntax and functionality of the HLSL shading language, making it easier for developers to write CPU-side code that mirrors GPU shader logic. It provides vector, matrix, and math operations with a syntax identical or very similar to HLSL, allowing seamless transition between shader code and application code. The library is optimized for performance and supports SIMD instructions across multiple architectures, including SSE,... -
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ChrysaLisp
Parallel OS, with GUI, Terminal, OO Assembler, Class libraries
ChrysaLisp is a 64-bit, MIMD, multi-CPU, multi-threaded, multi-core, multi-user parallel operating system with features such as a GUI, terminal, OO Assembler, class libraries, C-Script compiler, Lisp interpreter, debugger, profiler, vector font engine, and more. It supports MacOS, Windows, and Linux for x64, Riscv64, and Arm64 and eventually will move to bare metal. It also allows the modeling of various network topologies and the use of ChrysaLib hub nodes to join heterogeneous host networks. ... -
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Tracy Profiler
Frame profiler
A real-time, nanosecond resolution, remote telemetry, hybrid frame, and sampling profiler for games and other applications. Tracy supports profiling CPU (Direct support is provided for C, C++, Lua and Python integration. At the same time, third-party bindings to many other languages exist on the internet, such as Rust, Zig, C#, OCaml, Odin, etc.), GPU (All major graphic APIs: OpenGL, Vulkan, Direct3D 11/12, OpenCL.), memory allocations, locks, context switches, automatically attribute... -
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DALI
A GPU-accelerated library containing highly optimized building blocks
The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built-in data loaders and data iterators in popular deep learning frameworks. Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding,... -
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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... -
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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. Supported message protocol based on Fast Binary Encoding. -
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MNN
MNN is a blazing fast, lightweight deep learning framework
MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity... -
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Shumai
Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun
...The library supports matrix operations, gradient computation, and tensor conversions with intuitive APIs and near-native speed, thanks to Bun’s low-overhead FFI bindings. It can automatically leverage GPU acceleration on Linux (via CUDA) and CPU computation on macOS. -
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Intel PCM
Intel® Performance Counter Monitor (Intel® PCM)
Intel® Performance Counter Monitor (Intel® PCM) is an application programming interface (API) and a set of tools based on the API to monitor performance and energy metrics of Intel® Core™, Xeon®, Atom™ and Xeon Phi™ processors. PCM works on Linux, Windows, Mac OS X, FreeBSD, DragonFlyBSD and ChromeOS operating systems. -
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Halide
A language for fast, portable data-parallel computation
Halide is a programming language for fast, portable data-parallel computation. It was designed to make writing high-performance image and array processing code much easier on modern machines. It works on all major operating systems and with several CPU architectures (X86, ARM, MIPS, Hexagon, PowerPC) and GPU Compute APIs (CUDA, OpenCL, OpenGL, among others). It isn't a standalone programming language however; rather it is embedded in C++ which means that you write C++ code, building an... -
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mold
A Modern Linker
Mold is a modern high-performance linker designed as a drop-in replacement for traditional Unix linkers, with a primary goal of dramatically reducing build times for large software projects. In compiled languages like C, C++, and Rust, the linking phase can become a significant bottleneck, especially in large codebases, and mold addresses this by leveraging highly optimized algorithms and extensive parallelism. It is capable of utilizing all available CPU cores efficiently, resulting in... -
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VulkanSceneGraph
Vulkan & C++17 based Scene Graph Project
VulkanSceneGraph (VSG), is a modern, cross-platform, high-performance scene graph library built upon Vulkan graphics/compute API. The software is written in C++17 and follows the CppCoreGuidelines and FOSS Best Practices. The source code is published under the MIT License, with the exception of vulkan.h, used for Vulkan extensions, which is under Apache License 2.0. This repository contains C++ headers and source and CMake build scripts to build the libvsg library. Additional support... -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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CEmu emulator
Third-party TI-84 Plus CE / TI-83 Premium CE emulator
Developer-oriented emulator of the eZ80-based TI-84 Plus CE / TI-83 Premium CE calculators. CEmu is a third-party TI-84 Plus CE / TI-83 Premium CE calculator emulator, focused on developer features. The core is programmed in C and the GUI in C++ with Qt, for performance and portability reasons. CEmu works natively on Windows, macOS, and Linux! Easy setup - get running by doing a one-time-only connection of your calculator! Accurate and fast emulation. Customizable speed/throttling. Resizable... -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers,... -
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Perfetto
Production-grade client-side tracing, profiling, and analysis
Perfetto is a production-grade tracing platform for Android, Linux, and Chrome that captures extremely detailed information about what a system is doing over time. It’s designed around a low-overhead producer/consumer model: instrumented components (“producers”) write binary events into shared memory buffers and a collector (“service”) reliably streams them to storage. The data model spans kernel and userspace, so you can stitch together CPU scheduling, app lifecycles, binder/IPC hops, GPU work, power and thermal signals, file I/O, heap samples, and more into a single coherent timeline. ... -
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ArrayFire
ArrayFire, a general purpose GPU library
...Together we can fulfill The ArrayFire Mission under an excellent Code of Conduct that promotes a respectful and friendly building experience. Rigorous benchmarks and tests ensuring top performance and numerical accuracy. Cross-platform compatibility with support for CUDA, OpenCL, and native CPU on Windows, Mac, and Linux. Built-in visualization functions through Forge. -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
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POCO
Cross-platform C++ libraries for building network applications
The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++... -
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Faiss
Library for efficient similarity search and clustering dense vectors
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It... -
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Pixie
Instant Kubernetes-Native Application Observability
Pixie is an open-source observability tool for Kubernetes applications. Use Pixie to view the high-level state of your cluster (service maps, cluster resources, application traffic) and also drill down into more detailed views (pod state, flame graphs, individual full-body application requests). Pixie uses eBPF to automatically collect telemetry data such as full-body requests, resource and network metrics, application profiles, and more. Pixie collects, stores and queries all telemetry data...
