Search Results for "high performance computing"
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Showing 974 open source projects for "high performance computing"
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high-performance-go
high performance coding with golang
High Performance Go is an educational repository focused on writing faster and more memory-efficient Go programs. It teaches developers how to measure performance before attempting optimization. Benchmarking and pprof are used to identify bottlenecks and compare implementation choices. The material examines strings, slices, loops, reflection, empty structs, and memory alignment. -
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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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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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CUDA Python
Performance meets Productivity
...The toolkit also includes utilities for profiling, memory management, distributed computing, and numerical operations, making it suitable for scientific computing, AI, and data processing workloads. -
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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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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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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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MinIO
High performance object storage server compatible with Amazon S3 APIs
MinIO is a high performance object storage server that is API compatible with Amazon S3 cloud storage service. MinIO makes it easy to build high performance, cloud native data infrastructure for machine learning, analytics and application data workloads. It is incredibly fast, enabling object storage to operate as the primary storage tier for a diverse set of workloads. -
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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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CubeCL
Multi-platform high-performance compute language extension for Rust
CubeCL is a low-level compute language and compiler framework designed to simplify and optimize GPU programming for high-performance workloads, particularly in machine learning and numerical computing. It provides an abstraction layer that allows developers to write portable, hardware-efficient compute kernels without directly dealing with complex GPU APIs such as CUDA or OpenCL. CubeCL focuses on delivering predictable performance and composability by exposing explicit control over memory layouts, parallelism, and execution patterns while still maintaining a developer-friendly syntax. ... -
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CubeFS
cloud-native file store
...Supports multi-tenant management and provides fine-grained tenant isolation policies. Supports multi-level caching, and multiple high-performance replication protocols, and optimizes specific performance for small files. -
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Hertz
Go HTTP framework with high-performance and strong-extensibility
Hertz [həːts] is a high-usability, high-performance and high-extensibility Golang HTTP framework that helps developers build microservices. It was designed with reference to other open-source frameworks like fasthttp, gin, echo and combined with the internal requirements in ByteDance. At present, it has been widely used inside ByteDance. Nowadays, more and more microservices use Golang. -
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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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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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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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NVTX (NVIDIA Tools Extension Library)
C-based Application Programming Interface (API)
...It allows developers to insert markers, ranges, and events directly into their applications, providing contextual insight into how code executes on CPUs and GPUs. These annotations are visualized in tools such as NVIDIA Nsight Systems and Nsight Compute, enabling developers to identify performance bottlenecks, track execution flow, and correlate application behavior with hardware activity. The API is written in C and includes wrappers for C++ and Python, making it accessible across different programming environments and workloads. NVTX is particularly valuable in high-performance computing and AI workloads where understanding concurrency, memory usage, and kernel execution is critical for optimization. -
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FastAPI
FastAPI framework, high performance, easy to learn, fast to code
FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs. Get production-ready code. -
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FastAPI Python
FastAPI framework, high performance, easy to learn, fast to code
FastAPI framework, high performance, easy to learn, fast to code, ready for production. FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based on standard Python type hints. -
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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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Workerman
An asynchronous event driven PHP socket framework
...It has many high-performance components such as asynchronous Mysql, asynchronous Redis, asynchronous Http, MQTT Internet of Things client, and asynchronous message queue. Based on the high-performance Epoll event network library, a single machine can support millions of concurrent connections, with a long connection throughput of up to 36W/S. Objects such as PHP database can be resident in memory, reducing analysis and compilation and network overhead. -
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Peroxide
Rust numeric library with high performance and friendly syntax
...Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. For users familiar with numerical computing libraries like NumPy, MATLAB, or R, Rust's syntax might seem unfamiliar at first. This can make it more challenging to learn and use Rust libraries that heavily rely on Rust's unique features and syntax. -
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MetaCall Core
The ultimate polyglot programming experience
A polyglot runtime that enables seamless execution of multiple programming languages within the same environment, improving interoperability between different codebases. -
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HikariCP
A solid, high-performance, JDBC connection pool at last
HikariCP is a high-performance JDBC connection pooling library designed to offer minimal overhead and maximum throughput. It aims for simplicity and stability, concentrating on fast connection acquisition and minimal latency under load. Its internals manage a pool of connections aggressively but smartly, with options such as leak detection, timeout thresholds, and adaptive connection retirement. -
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Unified Communication X
Communication framework for data-centric high-performance applications
Accelerate Your Network Performance with UCX. Collaboration between industry, laboratories, and academia to create an open-source, production-grade communication framework for data-centric and high-performance applications. Unified Communication X (UCX) is an award winning, optimized production proven communication framework for modern, high-bandwidth and low-latency networks. -
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LoopVectorization.jl
Macro(s) for vectorizing loops
LoopVectorization.jl is a Julia package for accelerating numerical loops by automatically applying SIMD (Single Instruction, Multiple Data) vectorization and other low-level optimizations. It analyzes loops and generates highly efficient code that leverages CPU vector instructions, making it ideal for performance-critical computing in fields such as scientific computing, signal processing, and machine learning.
