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  2. GPU cluster - Wikipedia

    en.wikipedia.org/wiki/GPU_cluster

    A GPU cluster is a computer cluster in which each node is equipped with a graphics processing unit (GPU). By harnessing the computational power of modern GPUs via general-purpose computing on graphics processing units (GPGPU), very fast calculations can be performed with a GPU cluster. Titan, the first supercomputer to use GPUs

  3. System requirements - Wikipedia

    en.wikipedia.org/wiki/System_requirements

    The most common set of requirements defined by any operating system or software application is the physical computer resources, also known as hardware, A hardware requirements list is often accompanied by a hardware compatibility list (HCL), especially in case of operating systems.

  4. General-purpose computing on graphics processing units

    en.wikipedia.org/wiki/General-purpose_computing...

    Alea GPU, [19] created by QuantAlea, [20] introduces native GPU computing capabilities for the Microsoft .NET languages F# [21] and C#. Alea GPU also provides a simplified GPU programming model based on GPU parallel-for and parallel aggregate using delegates and automatic memory management.

  5. Heterogeneous System Architecture - Wikipedia

    en.wikipedia.org/wiki/Heterogeneous_System...

    Among its main features, HSA defines a unified virtual address space for compute devices: where GPUs traditionally have their own memory, separate from the main (CPU) memory, HSA requires these devices to share page tables so that devices can exchange data by sharing pointers. This is to be supported by custom memory management units.

  6. Compute Express Link - Wikipedia

    en.wikipedia.org/wiki/Compute_Express_Link

    Type 2 (CXL.io, CXL.cache and CXL.mem) – coherently access host memory and device memory, general-purpose accelerators (GPU, ASIC or FPGA) with high-performance GDDR or HBM local memory. Devices can coherently access host CPU's memory and/or provide coherent or non-coherent access to device local memory from the host CPU. [38]

  7. ROCm - Wikipedia

    en.wikipedia.org/wiki/ROCm

    ROCm is free, libre and open-source software (except the GPU firmware blobs [4]), and it is distributed under various licenses. ROCm initially stood for Radeon Open Compute platform; however, due to Open Compute being a registered trademark, ROCm is no longer an acronym — it is simply AMD's open-source stack designed for GPU compute.

  8. Nvidia DGX - Wikipedia

    en.wikipedia.org/wiki/Nvidia_DGX

    Announced and released on May 14, 2020. The DGX A100 was the 3rd generation of DGX server, including 8 Ampere-based A100 accelerators. [21] Also included is 15 TB of PCIe gen 4 NVMe storage, [22] 1 TB of RAM, and eight Mellanox-powered 200 GB/s HDR InfiniBand ConnectX-6 NICs. The DGX A100 is in a much smaller enclosure than its predecessor, the ...

  9. Memory virtualization - Wikipedia

    en.wikipedia.org/wiki/Memory_virtualization

    In both storage and server virtualization, the applications are unaware that the resources they are using are virtual rather than physical, so efficiency and flexibility are achieved without application changes. In the same way, memory virtualization allocates the memory of an entire networked cluster of servers among the computers in that cluster.