Search Results for "multicore"
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Showing 68 open source projects for "multicore"
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1
future
R package: future: Unified Parallel and Distributed Processing in R
...It allows R expressions to be scheduled for future evaluation, with the result retrieved later, in a way decoupled from the specific backend used. This lets code be written in a way that works with sequential execution, multicore, multisession, cluster, or remote compute backends, without changing the high-level code. It handles automatic exporting of needed global variables/functions, managing of packages, RNG, etc. Automatic detection and export of global objects and functions needed by future expressions, so the user doesn’t need to manage that manually. ... -
2
SteelMC
A Minecraft server in Rust focused on a strong foundation
SteelMC is an independent Minecraft Java Edition server implementation written in Rust. It aims to reproduce vanilla behavior while using modern multicore processors more efficiently. Gameplay updates remain synchronous, while chunk generation, lighting, packet processing, and chunk transmission can run outside the main server tick. Players can join persistent multiplayer worlds, move, interact with blocks, manage inventories, use commands, chat, and return to previously saved areas. ... -
3
TSNE-CUDA
GPU Accelerated t-SNE for CUDA with Python bindings
...Note the log scale on both the points and time axis, and that the scale of the x-axis is in thousands of points (thus, the values on the x-axis range from 1K to 10M points. Dashed lines on SkLearn, BH-TSNE, and MULTICORE-4 represent projected times. Projected scaling assumes an O(nlog(n)) implementation. -
4
OpenCL.jl
OpenCL Julia bindings
...This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous. -
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Codon
A high-performance, zero-overhead, extensible Python compiler
Codon is a high-performance Python compiler that compiles Python code to native machine code without any runtime overhead. Typical speedups over Python are on the order of 100x or more, on a single thread. Codon supports native multithreading which can lead to speedups many times higher still. The Codon framework is fully modular and extensible, allowing for the seamless integration of new modules, compiler optimizations, domain-specific languages and so on. We actively develop Codon... -
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gensim
Topic Modelling for Humans
Gensim is a Python library for topic modeling, document indexing, and similarity retrieval with large corpora. The target audience is the natural language processing (NLP) and information retrieval (IR) community. -
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HeavyDB
HeavyDB (formerly MapD/OmniSciDB)
HeavyDB is an open-source GPU-accelerated analytical database designed to perform extremely fast queries on large datasets. The system is built as a SQL-based relational columnar database engine that leverages modern hardware parallelism, including GPUs and multicore CPUs. Its architecture allows users to query datasets containing billions of rows in milliseconds without requiring traditional indexing, pre-aggregation, or sampling techniques. HeavyDB was originally developed as part of the OmniSci platform (formerly MapD) and is commonly used for large-scale analytics and geospatial data processing. ... -
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MongoDB Rust Driver
The official MongoDB Rust Driver
...Because it’s asynchronous by design, it works well with Rust async runtimes like Tokio and async-std, letting developers build highly concurrent networked services that efficiently use modern multicore hardware. The crate also includes BSON encoding and decoding that maps cleanly to Rust types, so developers can work with rich document structures while retaining Rust’s performance guarantees. -
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Prime number ( primenumbers )
Benchmark for 50 000 000 prime numbers as single and multicore
Simple source files and compiled JAR Java programs, for benchmark 50 000 000 cycle finding prime numbers. On Intel(R) Core(TM) i5-8600K CPU, Windows 10 20H2, i have 39 second on single core and 7,6 second on multi core. (PS: C++ multicore 6 second). Added C files for gcc compiler in Windows 10 and for Xcode C command line project in MacOS ( tested on Mac mini M2 with single core 16 to 25 sec and multicore 2,3 to 5 second by compiler -O switch). Surprise, same code in JavaScript for M2 chip in Safari: 12,5 sec single core and 3,3 sec multi core. Python version with numba and numpy on MacOS with M2: 3,78 sec, Intel Ultra 5 225F Linux Fedora 43 GNOME(*Intel): 3,64 sec., W11Intel: 3,73; Faster style in python, MacOS M2: 1,81 sec, *Intel & W11Intel: 2,02 sec.; Ultra faster style in python, MacOS M2: 1,24 s - 1,26 s - 1,34 s, *Intel: 1,48 s - 1,50 s, W11Intel: 1,53 - 1,63. -
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10
paraffin
Iterative and recursive parallelism generics for Ada 2005 and Ada 2012
A suite of Ada 2012 generics to facilitate iterative and recursive parallelism for multicore systems and provide safer recursion for single and multicore systems. Generics include Ravenscar compatible versions for real-time systems. Also Includes paraffinalia, which is a set of useful generics for parallel quicksort, fast fourier transform, function integration, prefix sum, and Red-Black trees -
11
LDPartEditor
Create and edit LDraw™ parts quick and easy.
...Minimum System Requirements: - OpenGL 2.1 compatible Graphics Card - Operating System (64-bit): Windows [7 or newer], Mac OS X [>=14], Linux [e.g. Linux Mint >=22] - CPU: Multicore-Processor e.g. Intel Core 2 Duo or AMD Athlon II (>2.0Ghz) - RAM: 4 GB - Video-Memory: 1 GB - Free Disk Space: 150 MB Recommended Requirements: - OpenGL 3.3 compatible Graphics Card - Operating System (64-bit): Windows 7,8,10,11, Mac OS X [>=14], Linux [e.g. Linux Mint >=22] - CPU: Multicore-Processor with 4 cores (or more) - RAM: >4 GB - Video-Memory: >1 GB - Free Disk Space: 512 MB The sourcecode is now hosted on GitHub here: http://nilsschmidt1337.github.io/ldparteditor/ -
12
ParDRe
Parallel tool to remove duplicate DNA reads
...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. There also exists a MapReduce counterpart of ParDRe, called MarDRe (see the link above). UPDATE: From version 2.0.5 ParDRe also provides support to remove only optical duplicates (and leave biologically interesting duplicates) as well as to work with compressed input/output with .gz format. -
13
QInterference
Double slit experiment visualization tool loving multicore processors
QInterference can visualize batch of double slit experiments. It can also solve it in radial as well as Cartesian coordinates and moreover it can simulate functionality the phase-array radar with the main-bundle deflection. -
14
ZeroMQ
ZeroMQ core engine in C++, implements ZMTP/3.1
...You can connect sockets N-to-N with patterns like fan-out, pub-sub, task distribution, and request-reply. It's fast enough to be the fabric for clustered products. Its asynchronous I/O model gives you scalable multicore applications, built as asynchronous message-processing tasks. It has a score of language APIs and runs on most operating systems. Libzmq is mainly written in C++98 with some optional C++11-fragments. For configuration either autotools or CMake is employed. For Linux users, pre-built binary packages are available for most distributions. ... -
15
Thrust
The C++ parallel algorithms library
Thrust is the C++ parallel algorithms library which inspired the introduction of parallel algorithms to the C++ Standard Library. Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. It builds on top of established parallel programming frameworks (such as CUDA, TBB, and OpenMP). It also provides a number of general-purpose facilities similar to those found in the C++ Standard Library. The NVIDIA C++ Standard Library is an open-source project; it is available on GitHub and included in the NVIDIA HPC SDK and CUDA Toolkit. ... -
16
MPI-dot2dot
A Parallel Tool to Find DNA Tandem Repeats on Multicore Clusters
MPI-dot2dot is a parallel tool to accelerate the identification of Tandem Repeats on multisequence datasetes. This tool receives as input a multisequence file with FASTQ or FASTA formats. It uses MPI processes and OpenMP threads to exploit the compute capabilities of multicore clusters. -
17
progrep
Utility to show live progress, status & stats for running simulations
...It shows % completed, time remaining, time elapsed, number of threads, MPI_Rank(if any), CPU usage & speed (FPS). The FPS measures may be used in benchmarking, e.g. while optimizing HPC algorithms for performance. progrep supports both single-threaded and parallel (multicore/multinode - e.g. OpenMP/MPI) jobs. progrep can also report for jobs running on remote hosts, e.g. jobs running on Linux Clusters. progrep works in client-server model. The server can be installed in your simulation source code with only 4 extra lines (API). When the progrep command is invoked, it queries this server as a client. progrep does not interfere with or slow down your simulation when not invoked. ... -
18
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. -
19
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. -
20
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. ... -
21
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. -
22
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. -
23
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
