Search Results for "parallel-sudoku-solver" - Page 2
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Showing 2100 open source projects for "parallel-sudoku-solver"
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Dagger.jl
A framework for out-of-core and parallel execution
Dagger.jl is a framework for out-of-core and parallel computing in Julia that allows users to construct and execute dynamic task graphs. It is designed for large-scale, distributed, and memory-efficient computations. Dagger supports lazy evaluation and scheduling across multiple threads or machines, enabling high-performance workflows for data processing, scientific computing, and machine learning. -
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101-0250-00
ETH course - Solving PDEs in parallel on GPUs
This course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering. -
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DL_POLY
General purpose classical molecular dynamics (MD) simulation software
DL_POLY is a general-purpose classical molecular dynamics simulation package developed at Daresbury Laboratory. It has evolved from older replicated-memory designs into a distributed-memory code suitable for modern parallel computing. The software can be built in serial form or with MPI for larger simulations. It is used for molecular modeling in chemistry, physics, materials science, and condensed-matter research. DL_POLY provides a mature simulation environment for studying atomic and molecular systems under classical force-field descriptions. Its main value is offering a long-running, research-grade MD package with a strong focus on parallel execution and general scientific use. -
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alphageometry
AI-driven neuro-symbolic solver for high-school geometry problems
...AlphaGeometry integrates a symbolic deduction engine with a transformer-based language model to propose and validate geometric constructions in a stepwise proof process. The DDAR solver focuses purely on rule-based reasoning, while AlphaGeometry enhances this by using a learned model to suggest auxiliary constructions when logical reasoning alone is insufficient. The repository includes pre-trained weights, vocabulary files, and detailed configuration options for reproducing experiments. -
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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... -
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Tulip.jl
Interior-point solver in pure Julia
Tulip is an open-source interior-point solver for linear optimization, written in pure Julia. It implements the homogeneous primal-dual interior-point algorithm with multiple centrality corrections and therefore handles unbounded and infeasible problems. Tulip’s main feature is that its algorithmic framework is disentangled from linear algebra implementations. This allows to seamless integration of specialized routines for structured problems. -
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Dask
Parallel computing with task scheduling
Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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Apache Beam
Unified programming model for Batch and Streaming
Apache Beam is an open source, unified programming model to define both batch and streaming data-parallel processing pipelines, as well as certain language-specific SDKs for constructing pipelines and Runners. These pipelines are executed on one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam is especially useful for Embarrassingly Parallel data processing tasks, and caters to the different needs and backgrounds of end users, SDK writers and runner writers. -
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prek
Better `pre-commit`, re-engineered in Rust
...By rewriting everything in Rust, prek delivers substantial performance gains and reduces disk usage while maintaining compatibility with existing .pre-commit-config.yaml setups, letting teams switch over without rewriting configurations. It’s optimized for modern workflows, supporting monorepos with workspace modes, parallel hook installation and execution, and native handling of common hook tasks without external runtimes. Because it ships as a single binary with no runtime dependencies and is already being adopted in large projects (like CPython, Apache Airflow, and FastAPI), prek is increasingly seen as a next-generation tool for developers who value performance, simplicity, and robust git hook automation. -
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vLLM
A high-throughput and memory-efficient inference and serving engine
vLLM is a fast and easy-to-use library for LLM inference and serving. High-throughput serving with various decoding algorithms, including parallel sampling, beam search, and more. -
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HunyuanVideo-I2V
A Customizable Image-to-Video Model based on HunyuanVideo
...It extends video generation so that given a static reference image plus an optional prompt, it generates a video sequence that preserves the reference image’s identity (especially in the first frame) and allows stylized effects via LoRA adapters. The repository includes pretrained weights, inference and sampling scripts, training code for LoRA effects, and support for parallel inference via xDiT. Resolution, video length, stability mode, flow shift, seed, CPU offload etc. Parallel inference support using xDiT for multi-GPU speedups. LoRA training / fine-tuning support to add special effects or customize generation. -
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Flow-Next
Plan-first AI workflow plugin for Claude Code, OpenAI Codex
Flow-Next is a workflow orchestration tool designed to manage complex processes by structuring tasks into organized and repeatable pipelines. It focuses on improving productivity by allowing users to define workflows that can be executed step by step or in parallel. The system emphasizes modularity, enabling tasks to be broken down into smaller components that can be reused across different workflows. It supports integration with various tools and services, making it adaptable to different environments. The project is designed to handle both simple and complex workflows, providing flexibility for a wide range of use cases. ... -
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mosaicml composer
Supercharge Your Model Training
...The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for both experimentation and production-scale development. It includes built-in support for distributed training strategies such as Fully Sharded Data Parallelism and standard Distributed Data Parallel execution, helping teams scale models without having to assemble as much infrastructure by hand. -
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Crawl4AI
Open-source LLM Friendly Web Crawler & Scraper
Crawl4AI is a high-performance, AI‑ready web crawler tailored for LLM data ingestion and RAG pipelines. It supports adaptive crawling heuristics (stopping when enough info is gathered), structured markdown output, and high-speed parallel execution. Designed to operate at scale with optional Docker deployment and framework integrations. -
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pgBadger
A fast PostgreSQL Log Analyzer
...It parses PostgreSQL logs and generates detailed, visually appealing HTML reports, helping DBAs and developers understand query performance, connection issues, and system bottlenecks. With support for incremental analysis, gzip-compressed logs, and parallel processing, pgBadger is ideal for monitoring and optimizing PostgreSQL database activity in production environments. -
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Circuitscape.jl
Algorithms from circuit theory to predict connectivity
Circuitscape is an open-source program that uses circuit theory to model connectivity in heterogeneous landscapes. Its most common applications include modeling the movement and gene flow of plants and animals, as well as identifying areas important for connectivity conservation. The new Circuitscape is built entirely in the Julia language, a new programming language for technical computing. Julia is built from the ground up to be fast. As such, this offers a number of advantages over the... -
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pi-subagents
Pi extension for async subagent delegation with truncation
...Built-in specialists handle tasks such as codebase scouting, external research, planning, implementation, review, context gathering, and second-opinion analysis. Child sessions can run in the foreground with streamed results or continue asynchronously as background jobs. Agents can be composed into sequential chains, parallel groups, reusable workflows, and more durable missions. Custom agent definitions control prompts, models, tools, skills, context inheritance, permissions, timeouts, and output behavior through Markdown frontmatter. The extension also provides observability, fleet management, session sharing, cost inspection, schedules, worktree isolation, and optional runtime permission controls. -
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HunyuanVideo
HunyuanVideo: A Systematic Framework For Large Video Generation Model
...The framework aims to push the boundaries of video generation quality, incorporating multiple innovative approaches to improve the realism and coherence of the generated content. Release of FP8 model weights to reduce GPU memory usage / improve efficiency. Parallel inference code to speed up sampling, utilities and tests included. -
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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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PRDownloader
A file downloader library for Android with pause and resume support
...PRDownloader gives callbacks for everything like onProgress, onCancel, onStart, onError and etc while downloading a file. Supports proper request canceling. Many requests can be made in parallel. All types of customization are possible. -
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LAMMPS
Public development project of the LAMMPS MD software package
...LAMMPS is script-driven, so users can define simulation geometry, force fields, integration methods, output, and analysis behavior through input files. Its main value is combining broad scientific flexibility with scalable parallel performance for complex molecular and mesoscale simulations. -
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golangci-lint
Fast linters Runner for Go
golangci-lint is a fast Go linters runner. It runs linters in parallel, uses caching, supports yaml config, has integrations with all major IDE and has dozens of linters included. ⚡ Very fast: runs linters in parallel, reuses Go build cache and caches analysis results. Yaml-based configuration. Integrations with VS Code, Sublime Text, GoLand, GNU Emacs, Vim, Atom, GitHub Actions. A lot of linters included, no need to install them. -
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LightGBM
Gradient boosting framework based on decision tree algorithms
LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle large-scale data. It’s become widely-used for ranking, classification and many other machine learning tasks. -
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pgsync
Postgres to Elasticsearch/OpenSearch sync
pgsync is a lightweight tool for syncing Postgres databases across environments, such as from production to staging. It allows selective table syncing, data masking, and parallel copying for fast and safe data migration. pgsync is ideal for developers who need realistic test data without exposing sensitive information. -
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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.
