Search Results for "multicore" - Page 2
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Showing 95 open source projects for "multicore"
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Accelerate
Embedded language for high-performance array computations
...Accelerate is a free, general-purpose, open-source library that simplifies the process of developing software that targets massively parallel architectures including multicore CPUs and GPUs. Embedded in the advanced functional programming language Haskell, Accelerate programs are declarative, statically-typed, pure, functional, and ready to exploit all of the performance of modern parallel hardware. The combination of a strong type system, high-level code, and interactive development environment, allows you to develop code quickly with the confidence that it is correct. -
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LoopMatcher
Find sequence-specific stem-loops in FASTA and GenBank files.
...Also, sequences in GenBank format can be downloaded directly from NCBI using the NCBI access ID. Requirements JAVA Runtime 8. It's highly recommended to have a multicore processor to process large sequences. * Currently, this version only runs in Windows x64. -
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...it plays with a random algorythm the midifiles in the "/automidi" folder (for now max 200 files) . autopiano runs on another thread than the main program to minimize overhead , especially on multicore cpus . to change midipiano sounds settings run /autopiano/brainpiano2_chung.exe
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Pharos
RTOS for Secure, Safe and Real-Time Systems
Pharos is a free open-source RTOS for secure, safe and real-time systems with the following characteristics: - Memory and enhanced time partitioning (TSP) - Native support for sporadic, periodic and aperiodic threads - Fixed-priority preemptive scheduler - Execution time protection (threads are prevented from executing for more time than they are configured to) - Small size (full image has ~100 to 300KiB text, ~30KiB data) - Hard real-time determinism - Fast critical sections - Prioritized nested interrupts - inter-partition communication with filters to protect unwanted access - Multicore support (RMP) - Supports ARM9, Cortex-A/R/M and Aarch64, RISC-V64 (64 bits) - The complete TestSuite (see below information) is run successfully for each platform in each release - Tested: more than 170 KLOC of requirement-based tests, executed for each board at each release - Up-to-date User Manual also available See our wiki page for more information. -
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PMCGPU
Parallel simulators for Membrane Computing on the GPU
...The objective of this project (PMCGPU) is to bring together all the researchers working on the development of parallel simulators for P systems, specially those using the GPU (e.g. CUDA, OpenCL, etc). Other parallel platforms are also welcome (multicore and manycore, FPGAs, etc). This project has been initiated by the Research Group on Natural Computing (Department of Computer Science and Artificial Intelligence, University of Seville). PMCGPU was born inside the P-Lingua project, of the same research group. PMCGPU is a GNU project, so all the applications developed within it are released under the GPLv3 license. ... -
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prll
A utility for parallelizing the execution of shell functions.
PRLL HAS MOVED TO GITHUB https://github.com/exzombie/prll A utility for parallelizing the execution of shell functions. Focuses on convenience in interactive use, but is just as usable in shell scripts. Put your multicore to good use, or combine prll with ssh to create an instant cluster. -
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MarDRe
MapReduce-based tool to remove duplicate DNA reads
...This tool allows bioinformatics to avoid the analysis of not necessary reads, reducing the time of subsequent procedures with the dataset. MarDRe is the Big Data counterpart of ParDRe (link above), which employs HPC technologies (i.e., hybrid MPI/multithreading) to reduce runtime on multicore systems. Instead, MarDRe takes advantage of the MapReduce programming model to significantly improve ParDRe performance on distributed systems, especially on cloud-based infrastructures. Written in pure Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for Big Data processing. -
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Batch Audio Convert
Command-line mass conversion of any directory tree of audio files.
...It requires the following software to be installed: - flac and metaflac (flac files only) - vorbis-tools (ogg files only) - faac and faad (aac files only) - lame and madplay (mp3 files only) - alac-decoder and mpeg4ip-utils (ALAC decode) - ffmpeg (ALAC encode, wma decode) - mplayer (wma decode) - mp4v2-utils (AAC, ALAC, WAV decode) BAC is now optimized for multiprocessing on multicore systems: a tunable number of cores can be used for simultaneous conversions. -
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Tiramisu
Polyhedral compiler for expressing fast and portable data algorithms
...The Tiramisu compiler is based on the polyhedral model thus it can express a large set of loop optimizations and data layout transformations. Currently, it targets (1) multicore X86 CPUs, (2) Nvidia GPUs, (3) Xilinx FPGAs (Vivado HLS) and (4) distributed machines (using MPI). It is designed to enable easy integration of code generators for new architectures. -
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Mini Psiphon Launcher with auto Reconnect in ~Mb. You can combine it with SSH, Proxifier and other to tunnel your connection or use own forwarder. #New Version: V-1.4
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DeepLearn
Implementation of research papers on Deep Learning+ NLP+ CV in Python
Welcome to DeepLearn. This repository contains an implementation of the following research papers on NLP, CV, ML, and deep learning. The required dependencies are mentioned in requirement.txt. I will also use dl-text modules for preparing the datasets. If you haven't use it, please do have a quick look at it. CV, transfer learning, representation learning. -
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PREESM provides a complete framework for fast prototyping. It generates a simulation and an optimized multiprocessor code from graph descriptions of algorithm and architecture. Please visit the project homepage at http://preesm.sourceforge.net.
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Open Event Machine
An event driven processing runtime for multicore
Deprecated - see new repository in GitHub instead: https://github.com/openeventmachine/em-odp Open Event Machine (OpenEM or EM) is an architectural abstraction and framework of an event driven multicore optimized processing concept originally developed for networking. It offers an easy programming concept for scalable and dynamically load balanced multicore data plane applications with a very low overhead run-to-completion principle. EM can run on bare metal for best performance or under an operating system with special arrangements. ... -
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CRUSH
Data reduction and imaging for select astronomical cameras
CRUSH is a pioneering reduction and imaging suite for many astronomical cameras operating at far-infrared, submillimeter and millimeter wavelengths, such as SHARC-2, SCUBA-2, LABOCA, GISMO, or SOFIA/HAWC+ (to name a few). -
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VcSpawn
Runs cl.exe/link.exe with low priority in MS VisualStudio
This application is intended to reduce running priority of MS Visual Studio compiler and linker processes. When you build a solution in Visual Studio (2013-2017), it can run multiple cl.exe / link.exe processes that consumes 100% even of multicore CPU. Those processes run with a normal priority and can make other application's work sluggish, even if the compilation is running in the background. This application substitutes native cl.exe / link.exe files and spawns them with a lower than normal priority. As a result any other processes get enough CPU time and reacts promptly. ... -
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JavaCá&Lá
A java middleware for HPC and IoT
The Java Cá&Lá (or just JCL - www.javacaela.org) is a middleware that integrates high performance computing (HPC) and Internet of things (IoT) in a unique API. It enables asynchronous remote method invocation and distributed shared memory services over multicore computer architectures or over multicomputer clusters. Sensing services are also feasible in JCL IoT version. An API for internal control enables collecting several times and memory usage of tasks submitted to the JCL cluster. Finally, a distributed map implementation adopts de Java Map interface, a common data structure for Java developers. ... -
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Chapel
a Productive Parallel Programming Language
Chapel is an emerging parallel programming language whose design and development are being led by HPE in collaboration with academia, computing labs, and industry. Chapel's goal is to improve the productivity of parallel programmers, from laptops to supercomputers. **Please note that Chapel development has moved to GitHub** -
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Leaf
A game server framework in Go (golang)
Leaf, written in Go, is a open-source game server framework aiming to boost efficiency both in development and runtime. Simple APIs. Leaf tends to provide simple and plain interfaces which are always best for use. Self-healing. Leaf always tries to salvage the process from runtime errors instead of leaving it to crash. Multi-core support. Leaf utilize its modules and leaf/go to make use of CPU resouces at maximum while avoiding varieties of side effects may be caused. Each module runs inside... -
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JSensor
high performance computing, Wireless Sensors Networks Simulators
...JSensor is a sensor network simulator implemented at Computer Science Department of Federal University of Ouro Preto (DECOM-UFOP), Brazil. In contrast to JSensor counterparts, it is designed to simulate millions of sensors in multicore and, in near future, multicomputer architectures. -
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JavaCá&Lá
A Java Distributed Shared Memory Middleware
How can we easily develop applications for multicore or multicomputer architectures? We frequently use middlewares for that problem, but they are often complex and less productive. This way, at DECOM-UFOP, we have a middleware, named JavaCa&La or just JCL, to build portable and scalable solutions over many high performance computer architectures. Our middleware APIs is simple, intuitive and designed for young and senior programmers who don’t have high performance programming skills. ... -
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MuffinEC
Multi-technology, INDEL aware error correction for NGS data
...It officially supports four technologies (Illumina, 454, ion Torrent and PacBio - experimental) and it also has a generic setup for others (old and/or new). It is released under LGPL version 3.0. MuffinEC can use multicore systems, thanks to its OpenMP implementation. We are developing the 2nd version of MuffinEC. The beta version is already available online. The changes are listed in the VERSION_HISTORY file. Please report any problem you may encounter at the email address specified in the README file. We really appreciate your help. -
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New Terrain and 3D Map System
a very lightweight advanced terrain-rendering and 3D map rendering sys
A very lightweight advanced terrain-rendering and 3D map rendering system. Minimal dependencies: OpenGL, SDL. It's distrib in 2-3 separate modules: 1. the C++ implementation of the terrain- and/or surface- rendering Algorithms I have developed: both a multithread and a non-multithread variant is relaeased. 2. Seme as at point 1. , but with a road-network rendering and collision-detection module I wrote before. It also adds some trees at the top of the terrain. (multitread vesion not... -
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ParDRR-MPI
Parallel Duplicate Read Remover with MPI
...This tool will let the users to avoid the analysis of not necessary reads, reducing the time of subsequent procedures with the dataset (e.g., assemblies, mappings, etc.). The tool is implemented with MPI in order to exploit the parallel capabilities of multicore clusters. It is faster than multithreaded counterparts (end of 2015) for the same number of cores and, thanks to the message-passing technology, it can be executed on clusters. -
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NCrypted
NCrypted - simple file encryption software with GPU support
NCrypted is a simple file encryption software. It is implemented on top of AES 128-bit algorithm. This software was designed to be as simple as possible, so you won't find any fancy, flashy gui elements or complicated advanced options. You can also use it directly from command line. NCrypted can automatically detect and take advantage of your NVidia graphics card to speed up the file processing. -
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MPJ Express is an implementation of an MPI-like API—standardized by the Java Grande forum—used to write parallel Java applications, which can execute on a variety of parallel platforms ranging from multicore processors to compute clusters/clouds.
