Posts avec #DistributedComputing

#DistributedComputing

Les posts publics sur X qui utilisent #DistributedComputing.

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  1. ray✓@raydistributed
    Ray operates at two levels: Ray Core, which scales Python functions and classes with tasks and actors, and its libraries, offering easy-to-use abstractions tailored for ML workloads. #Ray #ML #DistributedComputing
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    084816.6K
  2. Jiale Zhi✓@_calio
    Introducing Fiber, a new framework that made #DistributedComputing for AI simple. Now you can program the whole computer cluster and running thousands of workers easily with the standard multiprocessing API that you are familiar with. 1/2
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    1825
  3. Jess Sze@spkjess_jess
    Better algorithms, data structures, storage formats, or just a little bit of C/Fortran/Numba code might be enough to give you the 10x speed boost. #Parallelism and #DistributedComputing are expensive ways to accelerate your application.
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  4. Einstein@Home@EinsteinAtHome
    Another new publication w/ #CitizenScience & #DistributedComputing contributions from our volunteers: “Study of 72 Pulsars Discovered in the PALFA Survey: Timing Analysis, Glitch Activity, Emission Variability, and a Pulsar in an Eccentric Binary” 📄 -B
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  5. Kenneth Stanley✓@kenneth0stanley
    Pleased to announce Fiber, a platform designed to make #DistributedComputing for AI easy. Program a whole cluster with thousands of workers with just the standard multiprocessing API. (Enhanced POET used Fiber!)
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    1731
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