Showing 2 open source projects for "compiler"

View related business solutions
  • Paessler - Monitor Your Whole Network in Minutes Icon
    Paessler - Monitor Your Whole Network in Minutes

    Auto-discovery finds your devices and deploys pre-configured sensors instantly. No project plan required, just visibility from day one.

    Waiting weeks for a monitoring rollout isn't an option when infrastructure doesn't stop running. PRTG's auto-discovery scans your network and suggests from over 200 pre-configured sensor types, so you're watching servers, applications and devices within minutes, not after a multi-week deployment. Enterprise-strength monitoring, without the enterprise complexity. Start your free trial today.
    Start Free 30-Day Trial
  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New customers can spin up VMs, build with AI, and query data at no cost.

    Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
    Start Free
  • 1

    Prime number ( primenumbers )

    Benchmark for 50 000 000 prime numbers as single and multicore

    ...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.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2

    CLUE - C Learning Undergrad Environment

    Tools to support the learning of the C programming language

    CLUE (C Learning Undergraduate Environment) is a software allowing students to work on assignments in the C language while benefiting from support for peer testing, hyper-linked tutorials to help them understand compiler error messages, detection of "novice errors" with warnings hyper-linked to tutorials. Sponsored by National Science Foundation under award CCLI #0836863.
    Downloads: 25 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next