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  2. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    CuPy is a part of the NumPy ecosystem array libraries [7] and is widely adopted to utilize GPU with Python, [8] especially in high-performance computing environments such as Summit, [9] Perlmutter, [10] EULER, [11] and ABCI.

  3. OptiX - Wikipedia

    en.wikipedia.org/wiki/OptiX

    CUDA is only available for Nvidia's graphics products. Nvidia OptiX is part of Nvidia GameWorks . OptiX is a high-level, or "to-the-algorithm" API, meaning that it is designed to encapsulate the entire algorithm of which ray tracing is a part, not just the ray tracing itself.

  4. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    CUDA 9.0–9.2 comes with these other components: CUTLASS 1.0 – custom linear algebra algorithms, NVIDIA Video Decoder was deprecated in CUDA 9.2; it is now available in NVIDIA Video Codec SDK; CUDA 10 comes with these other components: nvJPEG – Hybrid (CPU and GPU) JPEG processing; CUDA 11.0–11.8 comes with these other components: [19 ...

  5. Nvidia CUDA Compiler - Wikipedia

    en.wikipedia.org/wiki/Nvidia_CUDA_Compiler

    CUDA code runs on both the central processing unit (CPU) and graphics processing unit (GPU). NVCC separates these two parts and sends host code (the part of code which will be run on the CPU) to a C compiler like GNU Compiler Collection (GCC) or Intel C++ Compiler (ICC) or Microsoft Visual C++ Compiler, and sends the device code (the part which will run on the GPU) to the GPU.

  6. Comparison of debuggers - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_debuggers

    macOS i386, x86-64 and AArch64, iOS, Linux, FreeBSD, NetBSD, Windows: No ? Apache License v2.0 with LLVM Exceptions 16.0.5, 2 June 2023 mdb: 1999 Solaris standard debugger (adb) successor Any compiled to machine code: Solaris: Yes (Memory debugger) ? CDDL: 2016 TotalView: 1998 Source code and memory serial and parallel debugger C++, C, CUDA ...

  7. PhysX - Wikipedia

    en.wikipedia.org/wiki/PhysX

    Nvidia started enabling PhysX hardware acceleration on its line of GeForce graphics cards [7] and eventually dropped support for Ageia PPUs. [8] PhysX SDK 3.0 was released in May 2011 and represented a significant rewrite of the SDK, bringing improvements such as more efficient multithreading and a unified code base for all supported platforms. [2]

  8. Basic Linear Algebra Subprograms - Wikipedia

    en.wikipedia.org/wiki/Basic_Linear_Algebra...

    The Intel Math Kernel Library, supporting x86 32-bits and 64-bits, available free from Intel. [7] Includes optimizations for Intel Pentium, Core and Intel Xeon CPUs and Intel Xeon Phi; support for Linux, Windows and macOS. [37] MathKeisan NEC's math library, supporting NEC SX architecture under SUPER-UX, and Itanium under Linux [38] Netlib BLAS

  9. Apache SystemDS - Wikipedia

    en.wikipedia.org/wiki/Apache_SystemDS

    New python bindings with supports for several builtins, matrix operations, federated tensors and lineage traces. Cuda implementation of cumulative aggregate operators (cumsum, cumprod etc.) New model debugging technique with slice finder. New tensor data model (basic tensors of different value types, data tensors with schema) [experimental]