Search Results for "high performance computing"
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Showing 2923 open source projects for "high performance computing"
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Minecraft High-Performance Redstone
A multithreaded Minecraft server built for redstone
A Minecraft 1.20.4 creative server built for Redstone. Each 256x256 plot runs on a separate thread, allowing for less lag, more concurrency, and many awesome extra features. MCHPRS is very different from traditional servers. Because this server is tailored to the use of computation redstone, many things that are a part of Vanilla Minecraft servers don't exist here. That being said, MCHPRS comes with many of its own unique features. -
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The Julia Programming Language
High-level, high-performance dynamic language for technical computing
Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. ... -
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Sogou C++ Workflow
C++ parallel computing and asynchronous networking engine
As Sogou`s C++ server engine, Sogou C++ Workflow supports almost all back-end C++ online services of Sogou, including all search services, cloud input method, online advertisements, etc., handling more than 10 billion requests every day. This is an enterprise-level programming engine in light and elegant design which can satisfy most C++ back-end development requirements. -
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NVIDIA Warp
A Python framework for accelerated simulation, data generation
NVIDIA Warp is a high-performance Python framework developed by NVIDIA for building and accelerating simulation, graphics, and physics-based workloads using GPU computing. It enables developers to write kernel-level code in Python that is automatically compiled into efficient CUDA kernels, combining ease of use with near-native performance. The framework is designed for applications such as robotics, reinforcement learning, physical simulation, and differentiable computing, where performance and flexibility are critical. ... -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
...TensorRT is built on CUDA®, NVIDIA’s parallel programming model, and enables you to optimize inference leveraging libraries, development tools, and technologies in CUDA-X™ for artificial intelligence, autonomous machines, high-performance computing, and graphics. With new NVIDIA Ampere Architecture GPUs, TensorRT also leverages sparse tensor cores providing an additional performance boost. -
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Quantum++
Modern C++ quantum computing library
...The main design factors taken in consideration were ease of use, high portability, and high performance. The library's simulation capabilities are only restricted by the amount of available physical memory. On a typical machine (Intel i5 8Gb RAM) Quantum++ can successfully simulate the evolution of 25 qubits in a pure state or of 12 qubits in a mixed state reasonably fast. -
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ObjectBox Go Database
Embedded Go Database, the fast alternative to SQLite, gorm, etc.
ObjectBox Go is a lightweight and high-performance embedded NoSQL database designed for Go applications, providing efficient data storage and retrieval with minimal overhead. -
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HDF5
Official HDF5® Library Repository
HDF5 (Hierarchical Data Format v5) is a widely-used data management library and file format for storing large and complex scientific data sets efficiently. -
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N64 Wasm
A web based N64 Emulator
...It focuses on accessibility, allowing users to play retro games on any device with a compatible browser. The emulator integrates input handling and rendering pipelines optimized for web performance. It also serves as a technical showcase of WebAssembly’s capabilities for high-performance applications. Overall, N64Wasm bridges retro gaming and modern web platforms. -
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Chitu
High-performance inference framework for large language models
Chitu is a high-performance inference engine designed to deploy and run large language models efficiently in production environments. The framework focuses on improving efficiency, flexibility, and scalability for organizations that need to run LLM inference workloads across different hardware platforms. It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations. ... -
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NumPy
The fundamental package for scientific computing with Python
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. ... -
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LinDB
LinDB is a scalable, high performance, high availability database
LinDB is a scalable, high-performance, high-availability distributed time series database. A single server could easily support more than one million write TPS; With fundamental techniques like efficient compression storage and parallel computing, LinDB delivers highly optimized query performance. The multi-channel replication protocol supports any amount of nodes, and ensures the system's availability. -
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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. -
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AssemblyScript
A TypeScript-like language for WebAssembly
...Its design bridges the gap between high-level scripting and low-level execution, allowing developers to achieve near-native performance without switching to languages like C or Rust. AssemblyScript integrates with the WebAssembly ecosystem, enabling seamless interaction with JavaScript through standard APIs. It is widely used in scenarios where performance and portability are essential, such as gaming, data processing, and edge computing. -
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TDengine
Open-source time-series database with high-performance and scalability
...TDengine’s innovative design and purpose-built storage engine outperforms other time-series databases for data ingestion, querying and data compression while significantly reducing storage and computing costs. TDengine’s native distributed architecture powers out-of-the-box scalability and high availability. Nodes can be added through simple configuration to achieve greater data processing power. In addition, this feature is open source. TDengine uses SQL as the query language, thereby reducing learning and migration costs, while adding SQL extensions to handle time-series data better, and supporting convenient and flexible schemaless data ingestion. -
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plow
A high-performance HTTP benchmarking tool
Plow is an HTTP(S) benchmarking tool, written in Golang. It uses excellent fast HTTP instead of Go's default net/http due to its lightning-fast performance. Plow runs at specified connections (option -c) concurrently and real-time records summary statistics, histogram of execution time and calculates percentiles to display on Web UI and terminal. It can run for a set duration( option -d), for a fixed number of requests(option -n), or until Ctrl-C is interrupted. The implementation of real-time computing Histograms and Quantiles using stream-based algorithms inspired by Prometheus with low memory and CPU bounds. so it's almost no additional performance overhead for benchmarking. -
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Apache SeaTunnel
SeaTunnel is a distributed, high-performance data integration platform
SeaTunnel is a very easy-to-use ultra-high-performance distributed data integration platform that supports real-time synchronization of massive data. It can synchronize tens of billions of data stably and efficiently every day, and has been used in the production of nearly 100 companies. There are hundreds of commonly-used data sources of which versions are incompatible. With the emergence of new technologies, more data sources are appearing. -
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PowerJob
Enterprise job scheduling middleware with distributed computing
PowerJob is an open-source distributed computing and job scheduling framework which allows developers to easily schedule tasks in their own application. Front-end page is provided and developers can manage their task, monitor the status, check the logs online, etc. Four timing strategies are supported, including CRON expression, fixed rate, fixed delay and OpenAPI which allows you to define your own scheduling policies, such as delaying execution. Four execution modes are supported,... -
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SIMD
C++ wrappers for SIMD intrinsics
SIMD is a C++ library that provides portable abstractions over SIMD (Single Instruction, Multiple Data) instructions, enabling developers to write high-performance vectorized code without dealing directly with architecture-specific intrinsics. SIMD instructions allow a single operation to be applied to multiple data elements simultaneously, significantly accelerating numerical and data-parallel computations. However, differences across CPU architectures and compilers make direct usage complex, which xsimd addresses by offering a unified API that maps efficiently to underlying hardware capabilities. ... -
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RuleGo
Component orchestration rule engine framework for Go
RuleGo is a high-performance, component-based rule engine implemented in Go. It’s lightweight, embeddable, orchestration-ready, and built for flexible composition of business logic into reusable components. No external middleware dependencies, efficient data processing and linkage on low-cost devices, suitable for IoT edge computing. Embedded and Standalone Deployment modes. -
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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. -
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Infinispan
Infinispan is an open source data grid platform
Infinispan is a distributed in-memory data grid and caching system designed for high-performance computing. It allows applications to scale dynamically by distributing data across multiple nodes, reducing latency and improving resilience. -
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ModelingToolkit.jl
Modeling framework for automatically parallelized scientific ML
ModelingToolkit.jl is a modeling language for high-performance symbolic-numeric computation in scientific computing and scientific machine learning. It then mixes ideas from symbolic computational algebra systems with causal and acausal equation-based modeling frameworks to give an extendable and parallel modeling system. It allows for users to give a high-level description of a model for symbolic preprocessing to analyze and enhance the model. -
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Hermit for Rust
Hermit for Rust
Hermit-RS is a Rust-based unikernel designed for high-performance and cloud computing applications. By combining the safety and concurrency features of Rust with the minimalistic approach of unikernels, Hermit-RS offers a secure and efficient runtime environment. It is particularly suited for running single-tenant applications directly on hypervisors or bare-metal hardware, reducing overhead and improving performance. -
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Anime4KCPP
A high performance anime upscaler
...It aims to provide both high-quality and high-performance. HDN mode can better denoise, HDN level is from 1 to 3, higher for better denoising but may cause blur and lack of detail. Cross-platform, building have already tested in Windows, Linux, and macOS.