Showing 18 open source projects for "parallel computing"

View related business solutions
  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
    Try free now
  • Automate contact and company data extraction Icon
    Automate contact and company data extraction

    Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.

    Generate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
    Explore Apify Store
  • 1
    101-0250-00

    101-0250-00

    ETH course - Solving PDEs in parallel on GPUs

    This course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2
    Dask

    Dask

    Parallel computing with task scheduling

    Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    The Julia Programming Language

    The Julia Programming Language

    High-level, high-performance dynamic language for technical computing

    Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. ...
    Downloads: 4 This Week
    Last Update:
    See Project
  • 4
    go-streams

    go-streams

    A lightweight stream processing library for Go

    A lightweight stream processing library for Go. go-streams provides a simple and concise DSL to build data pipelines. In computing, a pipeline, also known as a data pipeline, is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time-sliced fashion. Some amount of buffer storage is often inserted between elements.
    Downloads: 2 This Week
    Last Update:
    See Project
  • Say goodbye to broken revenue funnels and poor customer experiences Icon
    Say goodbye to broken revenue funnels and poor customer experiences

    Connect and coordinate your data, signals, tools, and people at every step of the customer journey.

    LeanData is a Demand Management solution that supports all go-to-market strategies such as account-based sales development, geo-based territories, and more. LeanData features a visual, intuitive workflow native to Salesforce that enables users to view their entire lead flow in one interface. LeanData allows users to access the drag-and-drop feature to route their leads. LeanData also features an algorithms match that uses multiple fields in Salesforce.
    Learn More
  • 5
    Lithops

    Lithops

    A multi-cloud framework for big data analytics

    Lithops is an open-source serverless computing framework that enables transparent execution of Python functions across multiple cloud providers and on-prem infrastructure. It abstracts cloud providers like IBM Cloud, AWS, Azure, and Google Cloud into a unified interface and turns your Python functions into scalable, event-driven workloads. Lithops is ideal for data processing, ML inference, and embarrassingly parallel workloads, giving you the power of FaaS (Function-as-a-Service) without vendor lock-in. ...
    Downloads: 4 This Week
    Last Update:
    See Project
  • 6
    LinDB

    LinDB

    LinDB is a scalable, high performance, high availability database

    LinDB is a scalable, high-performance, high-availability distributed time series database. A single server could easily support more than one million write TPS; With fundamental techniques like efficient compression storage and parallel computing, LinDB delivers highly optimized query performance. The multi-channel replication protocol supports any amount of nodes, and ensures the system's availability. Schema-free multi-dimensional data model with Metric, Tags, and Fields; The LinQL is flexible yet handy for real-time data analytics. Horizontal scalable is made simple by adding more new broker and storage nodes without too much thinking and manual operations. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 7

    PDP-OmniSim

    PDP-OmniSim simulating parallel and distributed processing systems

    PDP-OmniSim 🧬 Scientific Overview PDP-OmniSim is an advanced computational framework for simulating parallel and distributed processing systems, with cutting-edge applications in computational neuroscience, distributed computing, and complex systems modeling. The framework provides researchers with robust tools for large-scale simulations of networked systems and their emergent behaviors. 🎯 Key Scientific Contributions 🔬 Interdisciplinary Research Domains Computational Neuroscience: Large-scale neural population dynamics, brain-inspired computing architectures, and neuro-symbolic AI systems Distributed Systems: Scalable parallel processing simulations, resource allocation optimization, and fault-tolerant computing Complex Systems: Emergent behavior in networked systems, self-organizing criticality, and adaptive network topologies
    Downloads: 0 This Week
    Last Update:
    See Project
  • 8
    FileTrees.jl

    FileTrees.jl

    Parallel file processing made easy

    ...When computing lazy trees, these values are held in distributed memory and operated on in parallel.
    Downloads: 3 This Week
    Last Update:
    See Project
  • 9
    QuickRNASeq

    QuickRNASeq

    A pipeline for large scale RNA-seq data analysis

    We have implemented QuickRNASeq, an open-source based pipeline for large scale RNA-seq data analysis. QuickRNASeq takes advantage of parallel computing resources, a careful selection of previously published algorithms for RNA-seq read mapping, counting and quality control, and a three-stage strategy to build a fully automated workflow. We also implemented built-in functionalities to detect sample swapping or mislabeling in large-scale RNA-seq studies. Our pipeline significantly lifts large-scale RNA-seq data analysis to the next level of automation and visualization. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum Knight Icon
    Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum Knight

    Lock Down Any Resource, Anywhere, Anytime

    CLEAR by Quantum Knight is a FIPS-140-3 validated encryption SDK engineered for enterprises requiring top-tier security. Offering robust post-quantum cryptography, CLEAR secures files, streaming media, databases, and networks with ease across over 30 modern platforms. Its compact design, smaller than a single smartphone image, ensures maximum efficiency and low energy consumption.
    Learn More
  • 10
    Bat2015

    Bat2015

    Bachelor of Science (Informatik)

    ...With a focus on the MILP methods we implement a load balancing and speed up the solving process in a multiplicative way. Sometimes we have super-linear speedup with a small set of hardware. With a splitting of problems, parallel computing and distributing the actual best solution to all running processes we solve CBP much faster than a sequential processing can do.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 11

    Ezys

    Ezys 3D medical image registration program

    Ezys is a non-linear 3D medical image registration program. Ezys fully exploits the parallel computing power of inexpensive commercial graphics processing units (GPU), resulting in a very fast and accurate program capable of running on desktop PCs and even some laptops. On these systems, non-linear image registrations take less than a minute to complete. Ezys implements a diffeomorphic inverse consistent image registration algorithm with a demons-style regularization based on a non-parametric free form deformation model. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 12
    FlowVR
    FlowVR is an open source middleware tailored for high performance in situ data processing and analytics running on large parallel machines
    Downloads: 1 This Week
    Last Update:
    See Project
  • 13
    A scripting language and reference implementation to allow command line tools to be chained into complex parallel workflows.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 14
    Equalizer - Parallel Rendering
    Equalizer is the standard middleware to create parallel OpenGL-based applications. Please visit https://github.com/Eyescale for current development information.
    Leader badge
    Downloads: 25 This Week
    Last Update:
    See Project
  • 15
    Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming
    Downloads: 0 This Week
    Last Update:
    See Project
  • 16
    cca-forum
    Cca-forum unifies the Common Component Architecture tools and tutorial. It includes the CCA specifications, the Ccaffeine framework for HPC, and related tools. These support multilanguage scientific and parallel computing.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 17
    Shared Questionnaire System
    Shared Questionnaire System(SQS) is a full-functional Optical Mark Reader(OMR) form processing system implemented in Java-Swing, XSL-FO and AJAX with straightforward GUIs. It is aimed at developing social platform to share knowledge about questionnaire.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 18
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next