Search Results for "parallel-sudoku-solver" - Page 19
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Showing 1527 open source projects for "parallel-sudoku-solver"
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Parallel WaveGAN
Unofficial Parallel WaveGAN
Parallel WaveGAN is an unofficial PyTorch implementation of several state-of-the-art non-autoregressive neural vocoders, centered on Parallel WaveGAN but also including MelGAN, Multiband-MelGAN, HiFi-GAN, and StyleMelGAN. Its main goal is to provide a real-time neural vocoder that can turn mel spectrograms into high-quality speech audio efficiently. -
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...(Disclaimer: Processing time depends on compute hardware) Typical processing time for 100mb .las is about 2 seconds. 25mb .laz file process in about the same times. Files are processed in parallel using available CPU cores. Pre-built Windows x64 installer available at https://buymeacoffee.com/nathancrews/e/255641
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CAMPARI
Software for molecular simulations and trajectory analysis
We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model. CAMPARI is a joint package for performing and... -
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iX
Autonomous GPT-4 agent platform
...IX provides a flexible and scalable solution for delegating tasks to AI-powered agents. Agents created with the platform can automate a wide variety of tasks while running in parallel and communicating with each other. -
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SGE_GPU
Patch to SGE 2011.p1,Son of Grid Engine, multiple GPU, Linux
...Also, you need to set a consumable, named "ngpus". And assign value of it to each node. When submit GPU job, run: >qsub -l ngpus=1 ... This also works for parallel jobs. >qsub -pe openmpi 4 -l ngpus=1 ... Here, "-l ngpus=1" request 1 GPU for 1 process. It supports multiple GPU scheduling on nodes as well. For example, if node001 has 4 GPUs installed. JobA uses GPU0, JobB uses GPU2, and then JobC requestes 2 GPUs, it can dispatch GPU1 and GPU3 to JobC, and set the environment for the job on node001: CUDA_VISIBLE_DEVICES=1,3 For non-GPU jobs, it is set to empty. ... -
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IntegreSQL
IntegreSQL manages isolated PostgreSQL databases for your integration
IntegreSQL is a PostgreSQL clone provisioning tool that helps with testing by instantly spinning up database copies from a base template. It’s designed for integration tests where speed and data isolation are critical. IntegreSQL eliminates setup time and ensures a consistent database state across test runs. -
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Zoekt
Fast trigram based code search
...A built-in web UI and JSON API enable both interactive exploration and integration into editors and other tools. It supports ranking heuristics such as path weighting and symbol awareness to surface likely matches first, even in monorepos. Incremental and parallel indexing let it keep up with active codebases, making it suitable for both local deployments and multi-tenant service setups. -
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Kompute
General purpose GPU compute framework built on Vulkan
General purpose GPU compute framework built on Vulkan to support 1000s of cross-vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous, and optimized for advanced GPU data processing use cases. Backed by the Linux Foundation. -
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TensorHouse
A collection of reference Jupyter notebooks and demo AI/ML application
TensorHouse is a scalable reinforcement learning (RL) platform that focuses on high-throughput experience generation and distributed training. It is designed to efficiently train agents across multiple environments and compute resources. TensorHouse enables flexible experiment management, making it suitable for large-scale RL experiments in both research and applied settings. -
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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WordleSolver
Wordle Solver written in BASH
This Wordle solver is written in BASH, and filters through /usr/share/dict/words to narrow down the possible solutions. To use it, simply download the script and make it executable. " chmod u+x PATH/wordlesolver_VERSION.sh " This project was created with the intent to teach BASH programming to students in a fun and meaningful way.. Wordle is a trademark of its respective owners. -
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Functionary
Chat language model that can use tools and interpret the results
...Function definitions are typically provided in JSON schema format, allowing the model to generate structured function calls compatible with modern tool-calling interfaces used in AI applications. Functionary can decide whether to execute tools sequentially or in parallel and can analyze the outputs of those tools to produce context-aware responses. This capability allows AI systems to interact with external services, APIs, or computation engines rather than relying solely on knowledge embedded in the model. -
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The Huygens Remote Manager is an open-source, efficient, multi-user web-based interface to the Huygens software by Scientific Volume Imaging (http://www.svi.nl/) for parallel batch deconvolutions.
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ADAMS
ADAMS is a workflow engine for building complex knowledge workflows.
ADAMS is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes. Instead of placing operators on a canvas and manually connecting them, a tree structure and flow control operators determine how data is processed (sequentially/parallel). This allows rapid development and easy maintenance of large workflows, with hundreds or thousands of operators. Operators include machine learning (WEKA, MOA, MEKA) and image processing (ImageJ, JAI, BoofCV, LIRE and Gnuplot). R available using Rserve. WEKA webservice allows other frameworks to use WEKA models. Fast prototyping with Groovy and Jython. ... -
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YiVal
Your Automatic Prompt Engineering Assistant for GenAI Applications
YiVal is an open-source framework designed to automate prompt engineering and evaluation workflows for generative AI applications, enabling developers to systematically improve the performance of large language models. It focuses on experimentation and optimization by allowing users to test multiple prompt variations, configurations, and model parameters in parallel, then evaluate their outputs using structured metrics and scoring systems. The platform is particularly useful in production environments where prompt quality directly impacts user experience, as it provides a repeatable and data-driven approach to refining prompts rather than relying on manual trial and error. YiVal supports integration with various LLM providers and can orchestrate experiments across different models, making it adaptable to evolving AI ecosystems. ... -
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GatcomVideo
Graphical application included in the VDSF-VN framework
Application developed in Java that allow the study of video streaming over Vehicular Networks (VANETs), including all the necessary tasks, namely: video encoding with HEVC, launching the simulations in parallel, generating graphs with the results, and analysing the received video quality with several Quality of Experience (QoE) metrics: Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), ... GatcomVideo is part of the Video Delivery Simulation Framework over Vehicular Networks (VDSF-VN), which is composed of several components: (1) an OMNeT++ project called "ppp_qos" (2) GatcomSUMO (3) GatcomVideo The "ppp_qos" project and the application GatcomSUMO are downloadable from different SourceForge projects. ... -
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Statistical Rethinking 2023
Statistical Rethinking Course for Jan-Mar 2023
The 2023 edition modernizes and expands on the same curriculum, adjusting exercises and code for newer versions of R, Stan, and supporting packages. It continues to provide scripts for lectures and tutorials, while integrating refinements to examples, notation, and computational workflows introduced that year. Compared with 2022, some models are rewritten for clarity, and teaching materials reflect refinements in McElreath’s evolving presentation of Bayesian data analysis. Students following... -
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Given a partially filled 9×9 2D array, the goal is to assign digits (from 1 to 9) to the empty cells so that every row, column, and sub grid of size 3×3 contains exactly one instance of the digits from 1 to 9.
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SpiceDB
SpiceDB is the open source, Zanzibar-inspired authorization system
Open Source, Google Zanzibar-inspired permissions database to enable fine-grained access control for customer applications. Get started with the SpiceDB playground: https://play.authzed.com/ -
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VirtualGL
3D Without Boundaries
VirtualGL redirects 3D commands from a Unix/Linux OpenGL application onto a server-side GPU and converts the rendered 3D images into a video stream with which remote clients can interact to view and control the 3D application in real time. -
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VDSF-VN (ppp_qos)
Framework for simulation of video streaming over VANETs
Video Delivery Simulation Framework over Vehicular Networks (VDSF-VN) is a set of tools that allow the study of video streaming over Vehicular Networks (VANETs), including all the necessary tasks, namely: video encoding with HEVC, creating the network scenarios for SUMO & OMNeT++, launching the simulations in parallel, generating graphs with the results, analyzing the received video quality (PSNR, SSIM, ...). The framework is composed of several components: (1) an OMNeT++ project called "ppp_qos" (2) GatcomSUMO (3) GatcomVideo The applications GatcomSUMO and GatcomVideo are downloable from different SourceForge projects, and are developed in Java, so, they are platform independent, as well as the VDSF-VN framework. ... -
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Pget
The fastest, resumable file download client
Multi-Connection Download using parallel requests. This program comes with no warranty. You must use this program at your own risk. -
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Medusa
Framework for Accelerating LLM Generation with Multiple Decoding Heads
Medusa is a framework aimed at accelerating the generation capabilities of Large Language Models (LLMs) by employing multiple decoding heads. This approach allows for parallel processing during text generation, significantly enhancing throughput and reducing response times. Medusa is designed to be simple to implement and integrates with existing LLM infrastructures, making it a practical solution for scaling LLM applications. -
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PyTorch Implementation of SDE Solvers
Differentiable SDE solvers with GPU support and efficient sensitivity
This library provides stochastic differential equation (SDE) solvers with GPU support and efficient backpropagation. examples/demo.ipynb gives a short guide on how to solve SDEs, including subtle points such as fixing the randomness in the solver and the choice of noise types. examples/latent_sde.py learns a latent stochastic differential equation, as in Section 5 of [1]. The example fits an SDE to data, whilst regularizing it to be like an Ornstein-Uhlenbeck prior process. The model can be loosely viewed as a variational autoencoder with its prior and approximate posterior being SDEs. ... -
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LMAX Disruptor
High performance inter-thread messaging library
LMAX aims to be the fastest trading platform in the world. Clearly, in order to achieve this we needed to do something special to achieve very low-latency and high-throughput with our Java platform. Performance testing showed that using queues to pass data between stages of the system was introducing latency, so we focused on optimising this area. The Disruptor is the result of our research and testing. We found that cache misses at the CPU-level, and locks requiring kernel arbitration are... -
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Graph of Thoughts
Official Implementation of "Graph of Thoughts
...The framework executes these operations using a large language model as the reasoning engine while evaluating intermediate results to guide the search process. This approach enables models to explore multiple reasoning strategies in parallel and choose the most promising solutions during problem solving.
