Showing 3 open source projects for "cpu-g"

View related business solutions
  • Red Hat Enterprise Linux on Microsoft Azure Icon
    Red Hat Enterprise Linux on Microsoft Azure

    Deploy Red Hat Enterprise Linux on Microsoft Azure for a secure, reliable, and scalable cloud environment, fully integrated with Microsoft services.

    Red Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
  • Top-Rated Free CRM Software Icon
    Top-Rated Free CRM Software

    216,000+ customers in over 135 countries grow their businesses with HubSpot

    HubSpot is an AI-powered customer platform with all the software, integrations, and resources you need to connect your marketing, sales, and customer service. HubSpot's connected platform enables you to grow your business faster by focusing on what matters most: your customers.
  • 1
    Faiss

    Faiss

    Library for efficient similarity search and clustering dense vectors

    Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It...
    Downloads: 4 This Week
    Last Update:
    See Project
  • 2

    ThunderstormDistributor

    Distribute jobs to compute nodes on dynamic clusters

    ThunderstormDistributor is a queuing system that distributes jobs and computational workload across dynamic clusters in the cloud. It manages the assignment of jobs to maximize CPU and memory usage and prevent oversubscription of compute nodes. It also performs advanced statistics collection on individual compute nodes and jobs to graph the distribution of disk, network, CPU, and memory usage over time, which facilitates the advanced optimization and tuning of computational workflows.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    The project focuses on developing an environment where one can harness idle CPU cycles of numerous networked systems to work together on a particularly processing-intensive problem. (distributed computing you may call it)
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next