Search Results for "parallel-sudoku-solver" - Page 4
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936 projects for "parallel-sudoku-solver" with 1 filter applied:
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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PanSou
Network disk resource search API service that supports TG channel
PanSou is a high-performance cloud-storage resource search API built around concurrent Telegram and plugin-based discovery. It searches multiple configured sources in parallel and aggregates links into a normalized result format. Supported link categories include Baidu, Aliyun, Quark, Tianyi, UC, 115, PikPak, Xunlei, 123 Cloud, magnet links, ED2K, and others. Results are ranked using source priority, freshness, and keyword signals. An asynchronous plugin system allows new search providers to be added without changing the core service. ... -
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RuoYi Vue
Java rapid-development platform with separated architecture
RuoYi-Vue is an open-source Java rapid-development platform with separated frontend and backend architecture. Its backend uses Spring Boot, Spring Security, Redis, and JWT, with parallel branches for multiple Spring Boot generations. The classic frontend uses Vue, Element UI, Vuex, and Vue Router, while compatible Vue 3 variants are also available. It provides dynamic permission menus, role-based access control, multi-terminal authentication, and data-scope permissions. Built-in modules cover users, departments, positions, menus, roles, logs, scheduled jobs, monitoring, and system configuration. ... -
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AI Berkshire
AI-era Berkshire: a value investing research framework
...The project is meant to improve research depth, decision discipline, and analytical consistency compared with asking a general AI model for a one-off stock opinion. It uses parallel agent analysis, adversarial viewpoints, financial rigor checks, and repeatable report formats to reduce shallow or overly balanced conclusions. The framework covers company research, earnings review, industry screening, portfolio thinking, management analysis, and investment checklists. It is best understood as a research and decision-support system rather than a source of financial advice. -
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HumanLayer
Open source IDE for orchestrating AI coding agents in large codebases
HumanLayer is an open source development environment designed to help developers orchestrate and manage AI coding agents working within complex software projects. It provides a framework and tooling that allow AI agents to research, plan, and implement changes in large codebases while maintaining structured workflows. It focuses on enabling AI-assisted development through coordinated agent workflows rather than isolated code generation tasks. HumanLayer integrates with modern AI models and... -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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RealWorld
Exemplary fullstack Medium.com clone powered by React, Angular, Node
RealWorld is the “mother of all demo apps”—a full spec and starter backend/frontend that implements a Medium-like blogging platform to showcase best practices across many frameworks. Instead of trivial todo lists, it provides a realistic feature set: authentication, CRUD operations, pagination, comments, profiles, tagging, and favoriting. The same spec is realized dozens of times (React, Vue, Svelte, Angular, Solid, Next, Remix, and many more), alongside multiple server implementations, so... -
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YAPF
A formatter for Python files
YAPF is a Python code formatter that automatically rewrites source to match a chosen style, using a clang-format–inspired algorithm to search for the “best” layout under your rules. Instead of relying on a fixed set of heuristics, it explores formatting decisions and chooses the lowest-cost result, aiming to produce code a human would write when following a style guide. You can run it as a command-line tool or call it as a library via FormatCode / FormatFile, making it easy to embed in... -
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LLM Tornado
The .NET library to build AI agents with 30+ built-in connectors
...It provides a unified interface that connects to more than 30 AI providers and vector databases, allowing developers to switch between models and services without rewriting application logic. The framework introduces a powerful orchestration system based on graph-like structures, where agents, tasks, and transitions can be defined and executed in parallel or sequential flows. It supports multimodal inputs and outputs, including text, images, audio, and documents, making it suitable for a wide range of AI applications. LLMTornado also integrates advanced protocols such as Model Context Protocol and agent-to-agent communication, enabling complex interactions between systems. With built-in support for local deployments, enterprise guardrails, and observability features. -
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better-all
Better Promise.all with automatic dependency optimization
better-all is a TypeScript library that reinvents the familiar Promise.all construct by automatically analyzing and optimizing dependency graphs between asynchronous tasks, enabling maximal parallelization without manual orchestration. It addresses a common limitation where developers must manually refactor their promise chains to achieve efficient concurrency when some tasks depend on others, which can be error-prone and hard to maintain. With an object-based API, each task is declared as... -
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Atropos
Language Model Reinforcement Learning Environments frameworks
...It provides foundational tooling for asynchronous RL loops where environment services communicate with trainers and inference engines, enabling complex workflow orchestration in distributed and parallel setups. This framework facilitates experimentation with RLHF (Reinforcement Learning from Human Feedback), RLAIF, or multi-turn training approaches by abstracting environment logic, scoring, and logging into reusable components. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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GenStage
Producer and consumer actors with back-pressure for Elixir
...Its clear separation of concerns encourages testable, composable stages that can be rearranged as requirements evolve. In production, this leads to predictable, resilient dataflows for event ingestion, batching, and parallel processing. -
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NVIDIA AgentIQ
The NVIDIA AgentIQ toolkit is an open-source library
NVIDIA AgentIQ is an open-source toolkit designed to efficiently connect, evaluate, and accelerate teams of AI agents. It provides a framework-agnostic platform that integrates seamlessly with various data sources and tools, enabling developers to build composable and reusable agentic workflows. By treating agents, tools, and workflows as simple function calls, AgentIQ facilitates rapid development and optimization of AI-driven applications, enhancing collaboration and efficiency in complex... -
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Kamon Telemetry
Distributed Tracing, Metrics and Context Propagation for applications
...Just connect to your server and start tailing. But logs have a hard time showing you the overall response times for your application, or whether certain calls to the database are happening in sequence or parallel (among a million other things). -
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BeeAI Framework
Build production-ready AI agents in both Python and Typescript
...BeeAI also provides orchestration tools for designing dynamic workflows, enabling multiple agents to coordinate tasks through structured execution flows, retries, and parallel processing. -
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Fractals
Fractals is a recursive task orchestrator for agent swarm
Fractals is an experimental open-source framework designed to orchestrate complex tasks using swarms of AI agents organized in a recursive structure. The system takes a high-level goal and decomposes it into a hierarchy of smaller subtasks, forming a self-similar tree that resembles a fractal structure. Each leaf node of this tree represents a specific executable task that can be processed independently by an AI agent. The framework runs these subtasks in isolated Git worktrees so agents can... -
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Xtuner
A Next-Generation Training Engine Built for Ultra-Large MoE Models
...The framework focuses on enabling scalable training for extremely large models while maintaining efficiency across distributed computing environments. Unlike traditional 3D parallel training strategies, XTuner introduces optimized parallelism techniques that simplify scaling and reduce system complexity when training massive models. The engine supports training models with hundreds of billions of parameters and enables long-context training with sequence lengths reaching tens of thousands of tokens. Its architecture incorporates memory-efficient optimizations that allow researchers to train large models even when computational resources are limited. ... -
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Sandstorm
One API call, pull Claude agent, completely sandboxed
...This approach lowers the friction of building autonomous agents by removing the need to provision servers, orchestrate distributed agents, or manage persistent tooling; agents can be spun up in parallel without manual setup and shut down when complete. The sandbox environment isolates agent execution for security and predictability, and project updates continue to harden observability, fault handling, and configuration validation. -
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WorkAny
Desktop Agent for Any Task
...Powered by a combination of Claude Code as the primary runtime agent and a sandbox execution environment for safety, WorkAny integrates an agent SDK, MCP (Model Context Protocol) support, and custom skills to handle diverse tasks with contextual understanding. Users can connect multiple model providers, including OpenAI, OpenRouter, or custom endpoints, and WorkAny supports parallel task execution with asynchronous result viewing, enhancing productivity. -
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Step3-VL-10B
Multimodal model achieving SOTA performance
Step3-VL-10B is an open-source multimodal foundation model developed by StepFun AI that pushes the boundaries of what compact models can achieve by combining visual and language understanding in a single architecture. Despite having only about 10 billion parameters, it delivers performance that rivals or even surpasses much larger models (10×–20× larger) on a wide range of multimodal benchmarks covering reasoning, perception, and complex tasks, positioning it as one of the most powerful... -
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Docco
Literate Programming can be Quick and Dirty
Docco is a documentation generator by Jeremy Ashkenas that embraces the literate-programming style: it takes your source code and produces annotated HTML documentation that shows your comments side-by-side with your code. The idea is to read code like a book — commentary on one side, code on the other — which helps reviewers and learners understand intent and implementation simultaneously. It supports many languages (via configuration) and is intentionally quick and dirty, prioritizing... -
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LangExtract
A Python library for extracting structured information
...LangExtract supports a wide range of models, including Google Gemini, OpenAI GPT, and local LLMs via Ollama, making it adaptable to different deployment environments and compliance needs. The system excels at handling long documents using optimized chunking, multi-pass extraction, and parallel processing to ensure both high recall and structured consistency. -
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DeepEP
DeepEP: an efficient expert-parallel communication library
DeepEP is a communication library designed specifically to support Mixture-of-Experts (MoE) and expert parallelism (EP) deployments. Its core role is to implement high-throughput, low-latency all-to-all GPU communication kernels, which handle the dispatching of tokens to different experts (or shards) and then combining expert outputs back into the main data flow. Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP... -
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frugally-deep
A lightweight header-only library for using Keras (TensorFlow) models
...Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can run multiple predictions in parallel, thus utilizing as many CPUs as you like to improve the overall prediction throughput of your application/pipeline. -
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gradle-completion
Gradle tab completion for bash and zsh
Bash and Zsh completion support for Gradle. This provides fast tab completion for: Gradle tasks for the current project and sub-projects. Gradle CLI switches (e.g. --parallel). Common Gradle properties (e.g. -Dorg.gradle.debug) It also handles custom default build files, so rootProject.buildFileName = 'build.gradle.kts' is supported. See instructions for bash or for zsh, then consider optional additional configuration. Download and place the plugin and completion script into your oh-my-zsh plugins directory. ... -
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C-ARES
A C library for asynchronous DNS requests
This is C-ARES, an asynchronous resolver library. It is intended for applications that need to perform DNS queries without blocking, or need to perform multiple DNS queries in parallel. The primary examples of such applications are servers that communicate with multiple clients and programs with graphical user interfaces. The full source code is available in the 'C-ARES' release archives. -
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Argo Workflows
Workflow engine for Kubernetes
Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. Argo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition). Define workflows where each step in the workflow is a container. Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG). Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes. ...
