Search Results for "multi-thread cpu"
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Showing 56 open source projects for "multi-thread cpu"
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1
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 will not... -
2
CPU Features
A cross platform C99 library to get cpu features at runtime
...Implemented in portable C99, it is thread-safe, has no memory allocations, and raises no exceptions, making it suitable even for use in low-level system libraries. The design emphasizes portability, extensibility, and compatibility with sandboxed or restricted environments where direct CPU access may be limited. -
3
GPerftools
Fast, multi-threaded malloc() and nifty performance analysis tools
GPerftools (formerly Google Performance Tools) is a collection of a high-performance multi-threaded malloc() implementation, plus some pretty nifty performance analysis tools useful for creating more robust applications. These tools can be especially useful when developing multi-threaded applications in C++ with templates. Among these tools are TCMalloc, a thread-friendly heap-checker, heap-profiler and cpu-profiler. -
4
Unicorn Engine
Unicorn CPU emulator framework (ARM, AArch64, M68K, Mips, Sparc
Unicorn is a lightweight multi-platform, multi-architecture CPU emulator framework. Highlight features. Multi-architectures: ARM, ARM64 (ARMv8), m68k, MIPS, PowerPC, RISC-V, S390x (SystemZ), SPARC, TriCore & x86 (include x86_64). Clean/simple/lightweight/intuitive architecture-neutral API. Implemented in pure C language, with bindings for Pharo, Crystal, Clojure, Visual Basic, Perl, Rust, Haskell, Ruby, Python, Java, Go, D, Lua, JavaScript, .NET, Delphi/Pascal & MSVC available. ... -
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5
neo.mjs
The application worker driven frontend framework
...While current libraries/frameworks like Angular, React or Vue provide reasonable performance for small or mostly static Apps, they lack when it comes to big Apps or complex Components. The problem is, that most Apps today run within a single thread (CPU), while each computer or mobile device has several CPUs available. Some Apps move expensive tasks into separate threads, but this is by far not enough. Using neo.mjs, most parts of the framework as well as the Apps which you create with it, run inside a separate thread. This architecture leaves the main thread mostly idle, so it can fully concentrate on its purpose. -
6
Piscina
A fast, efficient Node.js Worker Thread Pool implementation
Piscina is a fast, efficient Node.js worker thread pool implementation, designed to perform heavy CPU-bound tasks in parallel, thereby improving application performance. -
7
ServiceTalk
A networking framework that evolves with your application
...Netty is a great low-level networking framework, but when used for service-to-service communication it presents a few opportunities for improvement. Fully asynchronous and requires knowledge of EventLoop threading model. Executing CPU-intensive or "blocking" code requires manual thread hops. Subtle out-of-order execution of tasks when code executes both on and off the EventLoop thread. APIs are not tailored towards common application use cases (e.g. request/response, RPC, etc..) The asynchronous programming paradigm presents a barrier to entry in scenarios where vertical scalability is not a primary concern. -
8
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. -
9
Lightweight ring buffer manager
Lightweight generic ring buffer manager library
The library provides generic FIFO ring buffer implementation. -
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10
cocoyaxi
A go-style coroutine library in C++11 and more
...It contains a series of high-quality base components, such as a go-style coroutine, coroutine-based network programming framework, command line, and config file parser, high-performance log library, unit testing framework, JSON library, etc. co has implemented a go-style coroutine, which has the following features. Multi-thread scheduling, the default number of threads is the number of system CPU cores. Shared stack, coroutines in the same thread share several stacks (the default size is 1MB), and the memory usage is low. Simple test on Linux shows that 10 millions of coroutines only take 2.8G of memory (for reference only). There is a flat relationship between coroutines, and new coroutines can be created from anywhere (including in coroutines). ... -
11
xManager
Ad-Free, New Features & Freedom
...Android devices have CPUs. Merged is a combination of Armeabi-v7a and Arm64-v8a architecture. Armeabi-v7a is the modern arch that supports floating point operations, and a multi-threading safe is used on multi-cpu devices. It is also 32-bit. If you are determined to run this on a non-android device then fire up an Android emulator. -
12
JMX Exporter
A process for exposing JMX Beans via HTTP for Prometheus consumption
JMX to Prometheus exporter: a collector that can configurable scrape and expose mBeans of a JMX target. This exporter is intended to be run as a Java Agent, exposing a HTTP server and serving metrics of the local JVM. It can be also run as a standalone HTTP server and scrape remote JMX targets, but this has various disadvantages, such as being harder to configure and being unable to expose process metrics (e.g., memory and CPU usage). Running the exporter as a Java agent is strongly... -
13
Netty-socketio
Socket.IO server implemented on Java
...Supports 0.7...0.9.16 (netty-socketio 1.6.6) and 1.0+ (netty-socketio latest version) version of Socket.IO-client. Supports distributed broadcast across netty-socketio nodes (Redisson, Hazelcast). Supports OSGi, supports Spring, lock-free and thread-safe implementation, and declarative handler configuration via annotations. YourKit is kindly supporting this open source project with its full-featured Java Profiler. YourKit, LLC is the creator of innovative and intelligent tools for profiling Java and .NET applications. CentOS, 1 CPU, 4GB RAM runned on VM, CPU 10%, Memory 15%, 6000 xhr-long polling sessions or 15000 websockets sessions, 4000 messages per second. -
14
Multimodal
TorchMultimodal is a PyTorch library
...The repository also includes example scripts and datasets for common multimodal tasks (e.g. retrieval, visual question answering, grounding) so you can test and compare models end to end. Installation supports both CPU and CUDA, and the codebase is versioned, tested, and maintained. -
15
DALI
A GPU-accelerated library containing highly optimized building blocks
...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, 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. ... -
16
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... -
17
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... -
18
Dockhand
Docker management you will like
Dockhand is a modern, self-hosted Docker management application that provides a graphical interface for handling container operations, Docker Compose stacks, and multi-environment orchestration without relying solely on terminal commands. Designed for homelab enthusiasts, developers, and growing teams, Dockhand offers real-time container lifecycle controls, visual editors for stacks, and a dashboard that shows system metrics like CPU and memory usage. The platform supports Git integration for deploying and syncing Compose stacks directly from repositories, interactive log streaming, and shell access into containers. ... -
19
DebugSwift
A toolkit to make debugging iOS applications easier
...Designed to operate within the iOS environment (iOS 14+ and Swift 6+), it includes network and WebSocket inspectors for HTTP requests, detailed performance metrics (CPU, memory, FPS), and mechanisms to detect memory leaks and main thread violations in real time. The toolkit also provides developers with crash analysis features, console log monitoring, device and build information displays, and customizable debugging panels, all of which make it easier to troubleshoot edge cases and unexpected behavior. ... -
20
Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. ... -
21
Perfetto
Production-grade client-side tracing, profiling, and analysis
...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. Perfetto’s ecosystem includes a web-based UI that can load multi-GB traces directly in the browser and an offline “trace processor” that exposes the trace as a queryable SQL-like table schema for deep analysis and automation. ... -
22
Bend
A massively parallel, high-level programming language
Bend is an interactive programming environment (REPL) built on top of the Kotlin language, designed to allow users to explore, experiment, and learn Kotlin in a live, feedback-driven manner. The tool lets you define variables, functions, or values at the prompt and iteratively refine them—immediately seeing output and types—while preserving state across commands. It emphasizes discoverability and experimentation: users can inspect functions, call them on sample inputs, and evolve logic... -
23
Hasktorch
Tensors and neural networks in Haskell
Hasktorch is a powerful Haskell library for tensor computation and neural network modeling, built on top of libtorch (the backend of PyTorch). It brings differentiable programming, automatic differentiation, and efficient tensor operations into Haskell’s strongly typed functional paradigm. This project is in active development, so expect changes to the library API as it evolves. We would like to invite new users to join our Hasktorch discord space for questions and discussions.... -
24
The Futhark Programming Language
A data-parallel functional programming language
...It is a statically typed, data-parallel, and purely functional array language in the ML family, and comes with a heavily optimizing ahead-of-time compiler that presently generates either GPU code via CUDA and OpenCL, or multi-threaded CPU code. Futhark is not designed for graphics programming, but can instead use the compute power of the GPU to accelerate data-parallel array computations. The language supports regular nested data-parallelism, as well as a form of imperative-style in-place modification of arrays, while still preserving the purity of the language via the use of a uniqueness type system. ... -
25
OpenCost
Cost monitoring for Kubernetes workloads and cloud costs
OpenCost is a vendor-neutral open-source project for measuring and allocating cloud infrastructure and container costs in real-time. Built by Kubernetes experts and supported by Kubernetes practitioners, OpenCost shines a light into the black box of Kubernetes spending. Flexible, customizable cost allocation and cloud resource monitoring for accurate showback, chargeback, and ongoing reporting. Dynamic asset pricing, through integrations with AWS, Azure, and GCP billing APIs as well as...
