Search Results for "high performance computing" - Page 19
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Showing 2509 open source projects for "high performance computing"
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Beef Programming Language
Beef Programming Language
Beef is a high-performance multi-paradigm open source programming language with a focus on developer productivity. The Beef Development Tools include an IDE with a general-purpose debugger capable of debugging native applications written in any language. The IDE supports productivity features such as autocomplete, fix-its, reformatting, refactoring tools, type inspection, hot compilation, and a built-in profiler. -
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Numba
NumPy aware dynamic Python compiler using LLVM
...Just apply one of the Numba decorators to your Python function, and Numba does the rest. Numba is designed to be used with NumPy arrays and functions. Numba generates specialized code for different array data types and layouts to optimize performance. Special decorators can create universal functions that broadcast over NumPy arrays just like NumPy functions do. Numba also works great with Jupyter notebooks for interactive computing, and with distributed execution frameworks, like Dask and Spark. -
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Fast CSV
CSV parser and formatter for node
A high-performance Node.js library for parsing and formatting CSV data efficiently. -
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how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
how-to-optim-algorithm-in-cuda is an open educational repository focused on teaching developers how to optimize algorithms for high-performance execution on GPUs using CUDA. The project combines technical notes, code examples, and practical experiments that demonstrate how common computational kernels can be optimized to improve speed and memory efficiency. Instead of presenting only theoretical explanations, the repository includes hand-written CUDA implementations of fundamental operations such as reductions, element-wise computations, softmax, and attention mechanisms. ... -
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OpenViking
Context database designed specifically for AI Agents
OpenViking is an open-source context database engineered for efficient indexing and retrieval of large amounts of unstructured or semi-structured context data used by AI applications. It’s primarily designed to serve as a high-performance, scalable backend for storing app context, embeddings, conversational histories, and other textual artifacts that need rapid lookup and semantic search, which makes it especially useful for systems like chatbots or memory-augmented agents. The project is implemented with performance in mind, often leveraging optimized data structures that balance fast reads and writes with minimal resource consumption. ... -
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RLax
Library of JAX-based building blocks for reinforcement learning agents
RLax (pronounced “relax”) is a JAX-based library developed by Google DeepMind that provides reusable mathematical building blocks for constructing reinforcement learning (RL) agents. Rather than implementing full algorithms, RLax focuses on the core functional operations that underpin RL methods—such as computing value functions, returns, policy gradients, and loss terms—allowing researchers to flexibly assemble their own agents. It supports both on-policy and off-policy learning, as well as value-based, policy-based, and model-based approaches. RLax is fully JIT-compilable with JAX, enabling high-performance execution across CPU, GPU, and TPU backends. ... -
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AWS ParallelCluster Node
Python package installed on the Amazon EC2 instances
aws-parallelcluster-node is the python package installed on the Amazon EC2 instances launched as part of AWS ParallelCluster. AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources and a shared filesystem and offers a variety of batch schedulers such as AWS Batch and Slurm. ... -
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MoonZoon
Rust Fullstack Framework
...It is built around a reactive programming model where UI updates are automatically triggered by changes in application state, reducing the need for manual DOM manipulation or complex state management patterns. The framework leverages WebAssembly for the frontend, allowing Rust code to run directly in the browser while maintaining high performance and type safety. On the backend, MoonZoon provides a server component that integrates seamlessly with the frontend, enabling efficient communication and shared logic across the application. It emphasizes simplicity and productivity by offering a cohesive architecture that minimizes boilerplate and promotes clear data flow. -
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SkyEmu
Game Boy Advance, Game Boy, Game Boy Color, and DS Emulator
SkyEmu is a modern, multi-system handheld emulator that supports Game Boy, Game Boy Color, Game Boy Advance, and experimental Nintendo DS emulation, with a strong focus on balancing accuracy, performance, and usability. It is designed as a low-level emulator that accurately reproduces hardware behavior while still offering a smooth and accessible user experience across a wide range of platforms. The emulator is highly portable, supporting desktop operating systems, mobile devices, and even... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Piral
Framework for next generation web apps using micro frontends
...Perfect for distributed systems running in the cloud. No proprietary software hijacking the security of your app. Every feature plays well with custom and standard tooling. The base layer gives you high convenience without sacrificing. Performance is considered important and valued as a feature. You can build fully dynamic and scalable applications in no time. Like what you see and want to take it to the next level? We have different support options and plans. Just contact us for an offer. -
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panicparse
Crash your app in style (Golang)
...Helps debugging crashes and deadlocks in heavily parallelized processes. Race detector support, e.g. it can parse output produced by go test -race. HTML export. Easy to use as an HTTP Handler middleware. High-performance parsing. HTTP web server that serves a very tight and swell snapshot of your goroutines, much more readable than net/http/pprof. >50% more compact output than original stack dump yet more readable. Deduplicates redundant goroutine stacks. Useful for large server crashes. Arguments as pointer IDs instead of raw pointer values. ... -
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Saleor Commerce
A modular, high performance, headless e-commerce platform
An open-source, GraphQL-first e-commerce platform delivering ultra-fast, dynamic and personalized shopping experiences. A headless, GraphQL commerce platform delivering ultra-fast, dynamic, personalized shopping experiences. Beautiful online stores, anywhere, on any device. Saleor is a rapidly-growing open source e-commerce platform that has served high-volume companies from branches like publishing and apparel since 2012. Based on Python and Django, the latest major update introduces a... -
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ONNX Runtime
ONNX Runtime: cross-platform, high performance ML inferencing
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators... -
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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). -
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EnvPool
C++-based high-performance parallel environment execution engine
EnvPool is a fast, asynchronous, and parallel RL environment library designed for scaling reinforcement learning experiments. Developed by SAIL at Singapore, it leverages C++ backend and Python frontend for extremely high-speed environment interaction, supporting thousands of environments running in parallel on a single machine. It's compatible with Gymnasium API and RLlib, making it suitable for scalable training pipelines. -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about 1 to 4. The library is tested regularly on MS Windows, Linux, and Mac OS X systems. No other packages are required to use the library, only APIs that are provided by an out of the box OS are needed. ... -
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RevoGrid
Powerful virtual data grid smartsheet with advanced customization
Support Millions of cells and thousands of columns easy and efficiently for fast data rendering. Easy to use. For large organizations managing massive datasets. Performance and scalability to handle even the most complex data tables. Rapid prototyping with intuitive and extendable codebase. Agility to build robust data-driven applications in no time. Quickly build elegant and efficient data grids. Lightweight yet powerful architecture lets you easily scale as your needs grow. -
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Carbon Language
Carbon Language's main repository
Carbon is an experimental successor to C++, developed by Google to serve as a modern, safer, and more evolvable systems programming language—designed to interoperate with C++ while providing clearer language design and tooling. Performance matching C++ using LLVM, with low-level access to bits and addresses. Interoperate with your existing C++ code, from inheritance to templates. Fast and scalable builds that work with your existing C++ build systems. -
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SpacetimeDB
Multiplayer at the speed of light
SpacetimeDB is a high-performance, distributed database optimized for real-time multiplayer applications. It offers low-latency data synchronization across clients, ensuring a seamless and responsive user experience. With built-in conflict resolution and support for complex data types, SpacetimeDB simplifies the development of interactive, collaborative applications. -
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AWS Powertools for Lambda
Powertools is a developer toolkit to implement best practices
A TypeScript utility library that provides best practices and tools for AWS Lambda applications. -
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ServiceStack
Simple, fast, versatile and full-featured services framework
...By using simple & pure dependency-free DTO models decoupled from any implementation we're free to continue layering on features which now sees ServiceStack APIs as the most versatile in the world where the same high-performance APIs can be consumed from HTTP in any combination of Route, QueryString, FormData or a myriad of data formats, via popular resilient MQ Servers whilst simultaneously supporting legacy integrations like SOAP or adopting new technologies like gRPC without sacrificing any native HTTP integrations. To maximize the value of APIs we're focused beyond the API boundary by making it as simple as possible for API Consumers to call your APIs. -
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GLM-4.7
Advanced language and coding AI model
GLM-4.7 is an advanced agent-oriented large language model designed as a high-performance coding and reasoning partner. It delivers significant gains over GLM-4.6 in multilingual agentic coding, terminal-based workflows, and real-world developer benchmarks such as SWE-bench and Terminal Bench 2.0. The model introduces stronger “thinking before acting” behavior, improving stability and accuracy in complex agent frameworks like Claude Code, Cline, and Roo Code. -
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JiT
PyTorch implementation of JiT
...Rather than predicting noise, JiT models directly predict clean image data, which the research suggests aligns better with the manifold structure of natural images and leads to stronger generative performance at high resolution. This implementation supports training on large datasets like ImageNet with configurable model variants, and practical scripts for setup, training, and evaluation on GPUs are included, leveraging PyTorch’s ecosystem for real-world experimentation. The repository’s layout contains modular engine, model, and training scripts enabling researchers and engineers to customize components such as training regimes, noise schedules, and evaluation routines. -
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Skiko
Kotlin Multiplatform bindings to Skia
...It serves as the low-level rendering backbone for Kotlin UI frameworks like Compose for Desktop and Compose for Web, enabling smooth, GPU-accelerated 2D graphics across Windows, macOS, Linux, and other supported targets without writing native code. Skiko abstracts away platform-specific rendering details while exposing Skia’s powerful features such as high-quality text shaping, image filters, path operations, and hardware accelerated canvases, making it ideal for building rich UI components, animations, games, or custom drawing surfaces. By leveraging Skia’s proven performance and cross-platform consistency, Skiko helps developers write a single graphics pipeline that behaves predictably across environments, simplifying maintenance and reducing platform fragmentation. -
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DifferentialEquations.jl
Multi-language suite for high-performance solvers of equations
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research which routinely outperform the “standard” C/Fortran methods, and include algorithms optimized...
