Search Results for "parallel-sudoku-solver" - Page 21
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Showing 1929 open source projects for "parallel-sudoku-solver"
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TFT_eSPI
Arduino and PlatformIO IDE compatible TFT library
...The library can be loaded using the Arduino IDE's Library Manager. Direct Memory Access (DMA) can be used with the ESP32, RP2040, and STM32 processors to improve rendering performance. "Four wire" SPI and 8 bit parallel interfaces are supported. Due to the lack of GPIO pins, the 8-bit parallel interface is NOT supported on the ESP8266. 8 bit parallel interface TFTs (e.g. UNO format mcufriend shields) can use with the STM32 Nucleo 64/144 range or the UNO format ESP32. ILI9341 and ST7796 SPI-based displays are recommended as starting points for experimenting with this library. ... -
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higgsfield
Fault-tolerant, highly scalable GPU orchestration
Higgsfield is an open-source, fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters, such as Large Language Models (LLMs). -
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LocustDB
Massively parallel, high performance analytics database
An experimental analytics database aiming to set a new standard for query performance and storage efficiency on commodity hardware. See How to Analyze Billions of Records per Second on a Single Desktop PC and How to Read 100s of Millions of Records per Second from a Single Disk for an overview of current capabilities. Download the latest binary release, which can be run from the command line on most x64 Linux systems, including Windows Subsystem for Linux. When loading .csv or .csv.gz files... -
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Django friendly finite state machine
Django friendly finite state machine support
Django-fsm adds simple declarative state management for Django models. If you need parallel task execution, view, and background task code reuse over different flows - check my new project Django-view flow. Instead of adding a state field to a Django model and managing its values by hand, you use FSMField and mark model methods with the transition decorator. These methods could contain side effects of the state change. -
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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protoactor-go
Proto Actor - Ultra fast distributed actors for Go, C# and Java/Kotlin
...The Actor Model provides a higher level of abstraction for writing concurrent and distributed systems. It alleviates the developer from having to deal with explicit locking and thread management, making it easier to write correct concurrent and parallel systems. Grain abstraction, which provides a straightforward approach to building distributed interactive applications, without the need to learn complex programming patterns for handling concurrency, fault tolerance, and resource management. This allows Proto.Actor to leverage in-process performance for realtime stream processing. -
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octelec - Electronics calculations
Electronics calculations in GNU Octave
...Select resistor or capacitor values from E3 to E192 series, convert two-port parameter sets, calculate operational characteristics (voltage gain, current gain, input impedance, output impedance) for two-port circuits connected to generator and load impedance, convert ratio to dB and vice versa, calculate parallel impedances, and round values to a number of significant leading digits. -
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Greenplum Database
Massive parallel data platform for analytics, machine learning and AI
Rapidly create and deploy models for complex applications in cybersecurity, predictive maintenance, risk management, fraud detection, and many other areas. With its unique cost-based query optimizer designed for large-scale data workloads, Greenplum scales interactive and batch-mode analytics to large datasets in the petabytes without degrading query performance and throughput. Based on PostgreSQL, Greenplum provides you with more control over the software you deploy, reducing vendor... -
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PANDA
A comprehensive and flexible quantification tool for proteomics data
...On the levels of spectra, peptides and proteins, PANDA works out a few quantitative filters and new scores for quantification confidence. Third, PANDA is designed for processing proteomics big data in parallel. -
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DPM-Solver
Fast ODE Solver for Diffusion Probabilistic Model Sampling
...The project introduces a specialized numerical solver designed to approximate the diffusion process using a small number of high-order integration steps. By reformulating the sampling problem as the solution of a diffusion-related ordinary differential equation, the solver can produce high-quality samples much more efficiently. This approach significantly reduces the computational cost required to generate images while maintaining strong generation quality. -
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IRBS - Institutional Registers Backup
Open Source Institutional Registers Backup Syst. for Paper Registers
...Just download the above zip file, extract it to a Disk Partition, with lots of free space & Turn ON Network Discovery By Right Clicking The Given Batch File To Run As Administrator ( Just Once ) Then double-click "START IRBS" file to start system. It opens up 2 browser tabs with login prompt, to help you make parallel entry into system, i.e. to maintain listbox reference data first & also your registers data next. 3 users present : operator, refsmanager & usermanager, for doing registry entry, listbox data entry & password change / create many operators respectively. Password for the users: i1r2b3s4 -
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OneFlow
OneFlow is a deep learning framework designed to be user-friendly
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous... -
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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. -
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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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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. ...
