41 skills found · Page 1 of 2
google-gemini / Genai ProcessorsGenAI Processors is a lightweight Python library that enables efficient, parallel content processing.
rofl0r / Jobflowdistribute and coordinate work using parallel processes (like GNU parallel, but much faster and memory-efficient)
3DStuff / VoxelizerParallel and memory efficient CPU rasterizer. Can process and merge multiple meshes to a single voxel model.
moonufo / GalaxyLight欢迎大家完善本系统，结合目前事务处理的精华，我开发了太极分布式事务处理框架MOONWATER，采用可靠消息服务和重试、补偿处理机制，使用事件驱动、最终一致的事务模型，巧妙地运用数据库的事务处理能力，对服务操作结果进行判断，调用应用系统自身的事务处理功能，自动进行事务处理，从而有效地解决微服务的分布式事务处理问题。框架采用消息机制调用服务，速度快、灵活，通过使用缓存，解决服务调用的冥等性和消息的冥等性，在事务处理时，采用异步并行调用对应的服务，提高了性能。MOONWATER是一个非常优秀的框架，优势在于提高了应用的成功率，自动进行分布式事务处理，事务处理速度快，提高了数据的一致性，把对事务的处理由不可控变为可控，需要人工处理的故障可一键完成，简单快捷，实现事务处理的自动化，框架提供SDK，开发使用方便，高效实用，可以支持任何微服务架构的项目，而且可以运用于任何其他项目，是一个业界领先的世界级成果，可以简单有效地实现CQRS+Event Sourcing领域模型DDD架构开发，及其他方式的微服务开发，实现一个路由灵活、数据可靠传输、高可用、高性能、易扩展的消息服务架构。 With the essence of the current transaction, I developed a Tai Chi distributed transaction processing framework MOONWATER, using reliable message service and retry, compensation mechanism, transaction model using event driven, a final agreement, the transaction processing database skillfully, to judge the service operation result, transaction processing function call application system itself. Automatic transaction processing, so as to effectively solve the problem of distributed transaction processing and micro services. Using the framework of message mechanism to invoke the service, fast and flexible, through the use of cache, solve the service invocation of the news and Ming Ming etc., in transaction processing, using asynchronous parallel call the corresponding service, improve the performance of. MOONWATER is an excellent framework, enhances the success rate of application, automatically distributed transaction processing, transaction processing speed, improve the consistency of the data, the handling of affairs by uncontrollable is controllable, fault need manual processing can be a key to complete, simple and quick, automated transaction the SDK provides a framework for development, use convenient, efficient and practical, can support any micro service architecture of the project, but also can be used in any other project, is an industry leading world-class achievements, can simply and effectively realize the development of DDD architecture CQRS+Event Sourcing domain model, and other means of micro service development, implementation a flexible routing, reliable data transmission, high availability, high performance and easy to extend message service architecture.Welcome everyone to improve the system,
rbga / CUDA Merge And Bitonic SortEfficient implementations of Merge Sort and Bitonic Sort algorithms using CUDA for GPU parallel processing, resulting in accelerated sorting of large arrays. Includes both CPU and GPU versions, along with a performance comparison.
photostructure / Batch Cluster.jsParallelized and efficient Node.js support for batch-mode child processes
radiuma-com / SlicerPySERAImplementation of PySERA in 3D Slicer
radaario / VoltageAn open-source, FFmpeg-based video encoding API that supports multiple concurrent instances. Easily scale video processing with parallel encoding, efficient resource management, and flexible API endpoints for a reliable, production-ready solution.
Cramraika / Tldv Downloader🎬 Fast TLDV video downloader with N_m3u8DL-RE support. Features batch downloads, parallel processing, session-based auth tokens, and automatic filename sanitization. Download single videos or entire meeting collections efficiently. Cross-platform Python script with smart fallback to FFmpeg.
nz / ElasticmillProcess your highly parallel Elasticsearch updates into efficient batches.
rohandhupar1996 / Fraud Detection ProductionProduction-ready fraud detection system using TensorFlow autoencoders with optimized CPU-GPU parallel processing. Features efficient ETL pipelines, Docker containerization, and TensorFlow Serving for deployment. Processes financial transactions in real-time with scalable inference capabilities.
nuniz / ParaFiltCollection of parallel adaptive filter implementations for efficient signal processing applications in PyTorch.
shaleenx / High Performance ComputingThis repository is dedicated to my course work on the DA-IICT course CS301: High Performance Computing. This repository contains three directories, namely Lab\ Work/ which is my collection of Lab Submissions undertaken as part of the course; 'High-Dimensional-Data-Clustering_HiPC_Parallel_Programming_Challenge_2015', which contains my team's submission in the Intel-Nvidia Parallel Programming Challenge as part of the High Performance Computing Conference Conference, Bangalore 2015, where my team comprised of myself, S. Chaitanya Prasad (@chaitanya94) and Visharad Bansal (@visharad-05); and my project submission for the course which was also on the same topic as the parallel programming challenge but this folder contains a much more detailed analysis. Today, nearly all computing systems including mobile phones, laptops, desktops, supercomputers, and large-scale data centers are being built using multiple-cors processors. Unlike the past, today almost all increases in system performance come from increased parallelism rather than increase in clock frequency. This shift to multi-core chips affects all segments of the IT industry and all areas of Computer Science. To efficiently work with these multi-core processors the users should acquire parallel programming and High Performance Computing (HPC) skills. HPC is also a key driver in the field of data science. This course was an introduction to parallel computing and aims at teaching basic models of parallel programming including the principles of parallel algorithm design, parallel computer architectures, programming models for shared and distributed-memory systems, message passing programming models used for cluster computing along with some important algorithms for parallel systems. Feel free to browse the repository. For any clarification, the author of the repo may be contacted at shaleen.k.gupta@gmail.com.
busyster996 / RustTunnyTunny is a flexible, efficient thread pool library for Rust built to manage and scale concurrent workloads. It enables you to process jobs in parallel across a configurable number of worker threads, supporting synchronous, asynchronous, and timeout-based job execution.
ayazhassan / RT CUDA GUI DevelopmentRecent development in Graphic Processing Units (GPUs) has opened a new challenge in harnessing their computing power as a new general-purpose computing paradigm with its CUDA parallel programming. However, porting applications to CUDA remains a challenge to average programmers. We have developed a restructuring software compiler (RT-CUDA) with best possible kernel optimizations to bridge the gap between high-level languages and the machine dependent CUDA environment. RT-CUDA is based upon a set of compiler optimizations. RT-CUDA takes a C-like program and convert it into an optimized CUDA kernel with user directives in a con.figuration .file for guiding the compiler. While the invocation of external libraries is not possible with OpenACC commercial compiler, RT-CUDA allows transparent invocation of the most optimized external math libraries like cuSparse and cuBLAS. For this, RT-CUDA uses interfacing APIs, error handling interpretation, and user transparent programming. This enables efficient design of linear algebra solvers (LAS). Evaluation of RT-CUDA has been performed on Tesla K20c GPU with a variety of basic linear algebra operators (M+, MM, MV, VV, etc.) as well as the programming of solvers of systems of linear equations like Jacobi and Conjugate Gradient. We obtained significant speedup over other compilers like OpenACC and GPGPU compilers. RT-CUDA facilitates the design of efficient parallel software for developing parallel simulators (reservoir simulators, molecular dynamics, etc.) which are critical for Oil & Gas industry. We expect RT-CUDA to be needed by many industries dealing with science and engineering simulation on massively parallel computers like NVIDIA GPUs.
labinnovationdocapost / OcrAutomatorTool based on Tesseract for parallelizing OCR, adding exifs in files efficiently and process big dataset
ocgears / OmnifilterAn image processing library designed on the theory of parallel processing to apply filters to photos extremely quickly and efficiently.
mominalix / GPU CPU Parallel AlgorithmsCutting-edge codes & resources for parallel computing, optimized algorithms, and efficient data processing in CUDA, OpenCL and OpenMP.
scriptlabs-cc / Discord Token CheckerFastest Discord Token Checker that verifies tokens and extracts account data (email/phone verification, Nitro status, billing). Features parallel processing, proxy support, and categorized results. Efficiently validates Discord accounts with a user-friendly interface.
905timur / File CorruptorA PowerShell script designed to randomly corrupt files in a specified directory by overwriting them with random data. The script supports parallel processing, logging, and progress tracking, making it efficient and user-friendly.
