Search Results for "hpc code analysis" - Page 13
Sort By:
Showing 1315 open source projects for "hpc code analysis"
View related business solutions-
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.
-
$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.
-
1
ai-cookbook
Examples and tutorials to help developers build AI systems
...Developers can learn how to construct applications like intelligent assistants, automation pipelines, and AI-powered data analysis tools through step-by-step tutorials and ready-to-run scripts. The code examples are designed to emphasize practical architecture patterns that are commonly used in production environments, helping developers understand how to integrate AI services into software products. -
2
Monolog
Sends logs to files, sockets, inboxes, databases and web services
Monolog sends your logs to files, sockets, inboxes, databases and various web services. See the complete list of handlers below. Special handlers allow you to build advanced logging strategies. This library implements the PSR-3 interface that you can type-hint against in your own libraries to keep a maximum of interoperability. You can also use it in your applications to make sure you can always use another compatible logger at a later time. As of 1.11.0 Monolog public APIs will also accept... -
3
learn_python3_spider
Python crawler tutorial series, learning Python crawlers from 0 to 1
...Data can be stored with CSV, MySQL, or MongoDB examples. More advanced material explores anti-scraping defenses, JavaScript analysis, WebSocket data, and distributed crawlers. The repository includes practical source-code examples for scraping several real-world websites and services. -
4
Big-AGI
AI suite powered by state-of-the-art models and providing advanced AI
Big-AGI is a comprehensive, open-source AI workspace built to serve as a powerful multi-model interface for developers, researchers, and professionals who want deep control over generative AI workflows and outputs. It unifies access to multiple large language models (LLMs) and AI services through a modern web UI that emphasizes efficient interaction, flexibility, and extensibility, enabling users to conduct multi-model chats, execute code, generate images, and perform voice or text-based... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
5
BrowserOS
Agentic browser; privacy-first alternative to ChatGPT Atlas
BrowserOS is an open-source, agentic web browser built on a Chromium base that integrates AI agents directly into the browsing experience. Rather than just doing standard browsing, it places AI intelligence at the core: you can connect your own API keys (for e.g., OpenAI, Anthropic, Google Gemini) or run local models (via e.g., Ollama) so that your browsing data and automation stay on your machine — privacy and control are emphasized throughout. The interface remains familiar to users of... -
6
tapjs
Test Anything Protocol tools for node
...An easily extensible TAP test framework, with outstanding TypeScript support, a CLI, plenty of assertion methods, snapshots, object/method spies, module mocking, file system fixtures, lifecycle hooks, test filtering, comprehensive code coverage analysis, color-accessible test reporters, and more. Software testing is a software and user experience design challenge that balances on the intersection of many conflicting demands. -
7
AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run... -
8
AI Engineer Coach
Better agentic engineering
AI Engineering Coach is a Microsoft VS Code extension for analyzing AI coding assistant usage across local session logs. It is designed to help developers improve how they work with tools such as VS Code, Claude, Codex, OpenCode, GitHub Copilot for Xcode, and Copilot CLI. The extension reads local logs and turns them into dashboards, practice scores, trends, anti-pattern detection, and actionable feedback. It focuses on agentic engineering habits such as prompt quality, context management,... -
9
Claude Subconscious
Give Claude Code a subconscious
...The plugin injects relevant context and guidance back into Claude before each prompt, effectively “whispering” insights that improve continuity and decision-making. It also has access to tools such as file reading, code search, and web browsing, enabling it to perform background analysis and augment responses with deeper context. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
10
Kodezi Chronos
Kodezi Chronos is a debugging-first language model
Kodezi Chronos is a research project focused on developing a specialized language model designed specifically for debugging software and understanding large code repositories. Unlike general-purpose language models that focus primarily on code generation, Chronos is built to diagnose and repair bugs by analyzing complex relationships across files within a codebase. The project introduces architectural techniques such as Adaptive Graph-Guided Retrieval, which allows the system to navigate... -
11
Integuru v0
The first AI agent that builds permissionless integrations
Integuru is an open-source AI agent designed to automatically create integrations between software platforms by reverse-engineering their internal APIs. Instead of relying on official developer documentation or publicly available APIs, the system analyzes network traffic generated by user interactions within a web application. Developers capture browser requests and authentication data, which the agent then uses to infer the structure of the platform’s internal API endpoints. Based on this... -
12
Logos
Create ridiculously fast Lexers
Logos is a lexer generator for Rust, designed to create fast and efficient lexers with minimal code. It leverages Rust's procedural macros to define token patterns, streamlining the process of lexical analysis. -
13
fvcore
Collection of common code shared among different research projects
fvcore is a lightweight utility library that factors out common performance-minded components used across Facebook/Meta computer-vision codebases. It provides numerics and loss layers (e.g., focal loss, smooth-L1, IoU/GIoU) implemented for speed and clarity, along with initialization helpers and normalization layers for building PyTorch models. Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. A... -
14
A.I.G (AI-Infra-Guard)
A full-stack AI Red Teaming platform securing AI ecosystems
...It combines scanning for AI agents, agent skills, MCP servers, AI infrastructure, and OpenClaw deployments. Its infrastructure scanner fingerprints AI services and checks them against a large library of known vulnerabilities. Agent and skill analysis detects risks involving malicious instructions, unsafe code execution, privilege abuse, compromised tools, and insecure dependencies. Jailbreak evaluation tests language models against multiple prompt-based attack methods and enables cross-model comparison. The platform also provides a web interface, standalone scanning tools, APIs, Docker deployment, and integrations for incorporating security checks into AI workflows. -
15
NLP
Open source NLP guide with models, methods, and real use cases
...It also introduces topic modeling with LDA, keyword extraction techniques, and document similarity methods. NLP extends into real-world applications, including sentiment analysis and text classification, helping readers connect concepts to use cases. Designed for accessibility, the project evolves over time, allowing updates and improvements as NLP techniques advance. It reflects a practical approach to learning, where readers can explore code, experiment with models, and build foundational skills in machine learning-driven language processing. -
16
papermill
Parameterize, execute, and analyze notebooks
...Instead of manually opening and running a notebook inside JupyterLab or Notebook every time, Papermill lets you inject new values into a specially tagged parameters cell and execute the entire notebook automatically via a script or automation pipeline, which enables robust automation of data analysis, reports, and experiments. This capability is particularly useful in data science and analytics, where a template notebook might be reused for batching reports across dates, customers, or other variables without rewriting code or duplicating notebooks. Papermill supports both Python API usage and a command-line interface, making it flexible for integration with CI/CD systems, shells, and workflow orchestration tools like Airflow. -
17
A.I.G (AI-Infra-Guard)
Full-stack AI Red Teaming platform
AI-Infra-Guard is a powerful open-source security platform from Tencent’s Zhuque Lab designed to assess the safety and resilience of AI infrastructures, codebases, and components through automated scanning and evaluation tools. It brings together AI infrastructure vulnerability scanning, MCP server risk analysis, and jailbreak evaluation into a unified workflow so that enterprises and individuals can identify critical security issues without relying on external services. Users can deploy it... -
18
LeetCode Master
About "Code Thoughts" LeetCode Practice Guide: 200 classic questions
leetcode-master is a comprehensive collection of LeetCode solutions written in C++ and organized as a structured learning path for coding interview preparation. The repository contains detailed explanations, categorized problem sets, and step-by-step reasoning behind solutions, making it an effective study companion for developers preparing for technical interviews. Problems are grouped by topic—such as arrays, linked lists, dynamic programming, greedy algorithms, and graph theory—so... -
19
ncc
Compile a Node.js project into a single file
Simple CLI for compiling a Node.js module into a single file, together with all its dependencies, gcc-style. Publish minimal packages to npm. Only ship relevant app code to serverless environments Don't waste time configuring bundlers, it is generally faster bootup time and less I/O overhead. Compiled language-like experience (e.g.: go). For testing and debugging, a file can be built into a temporary directory and executed with full source maps support. Some packages may need some extra options for ncc support in order to better work with the static analysis. ... -
20
a-stock-data
Full-stack China A-Share data toolkit for AI coding assistants
...The project organizes data across multiple layers, including market quotes, research reports, signals, capital flows, news, announcements, macro data, and financial statements. It is designed to work with tools such as Claude Code, Codex, and OpenClaw through context-injected Markdown and embedded Python. The repository emphasizes tested endpoints and practical usability for agent-driven financial analysis workflows. Its main value is turning fragmented A-share data sources into a unified toolset for AI-assisted research and coding. -
21
SkillForge
Ultimate meta-skill for generating best-in-class Claude Code skills
SkillForge is a systematic methodology and tooling framework for creating high-quality AI “skills” specifically optimized for Claude Code integrations, treating skill creation as an engineering discipline rather than an ad-hoc art form. It introduces a multi-phase architecture where every input or request is triaged intelligently, analyzed deeply through structured lenses, specified formally, synthesized with automated generation, and finally subjected to multi-agent review before... -
22
Suna
Suna - Open Source Generalist AI Agent
Suna is an open-source generalist AI agent developed by Kortix AI. Designed to assist users in accomplishing real-world tasks through natural conversation, Suna combines powerful capabilities with an intuitive interface. It serves as a digital companion for research, data analysis, and everyday challenges, integrating tools like browser automation, file management, web crawling, command-line execution, website deployment, and API integration. Suna's architecture comprises a FastAPI-based... -
23
Claude Scientific Skills
A set of ready to use Agent Skills for research, science, engineering
Claude Scientific Skills is a large open source collection of ready-to-use scientific capabilities that extend AI coding agents into full research assistants. The project provides more than 170 curated skills covering domains such as genomics, drug discovery, medical imaging, physics, and advanced data analysis. Each skill bundles documentation, examples, and tool integrations so agents can reliably execute complex multi-step scientific workflows. The framework follows the open Agent Skills standard and works with multiple AI development environments including Claude Code, Cursor, and Codex. Its primary goal is to reduce the friction of scientific computing by giving AI agents structured access to specialized libraries, databases, and research pipelines. ... -
24
Optopsy
A nimble options backtesting library for Python
Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. Optopsy is a small simple library that offloads the heavy work of backtesting option strategies, the API is designed to be simple and easy to implement into your regular Panda's data analysis workflow. ... -
25
Llama Cookbook
Solve end to end problems using Llama model family
The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models
