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Format name Design goal Compatible with other formats Self-contained DNN Model Pre-processing and Post-processing Run-time configuration for tuning & calibration
The setp.cc.type instruction sets a predicate register to the result of comparing two registers of appropriate type, there is also a set instruction, where set.le.u32.u64 %r101, %rd12, %rd28 sets the 32-bit register %r101 to 0xffffffff if the 64-bit register %rd12 is less than or equal to the 64-bit register %rd28. Otherwise %r101 is set to ...
In computing, CUDA is a proprietary [1] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.
In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...
touchHLE is a compatibility layer (referred to as a “high-level emulator”) for Windows and macOS made by Andrea "hikari_no_yume" (Sweden) in early 2023 to run legacy 32-bit iOS software. The compatibility layer was only able to run one software, Super Monkey Ball as of version 0.1.0.
Nvidia NVDEC (formerly known as NVCUVID [1]) is a feature in its graphics cards that performs video decoding, offloading this compute-intensive task from the CPU. [2] NVDEC is a successor of PureVideo and is available in Kepler and later NVIDIA GPUs.
In computing, Windows on Windows (commonly referred to as WOW) [1] [2] [3] is a discontinued compatibility layer of 32-bit versions of the Windows NT family of operating systems since 1993 with the release of Windows NT 3.1, which extends NTVDM to provide limited support for running legacy 16-bit programs written for Windows 3.x or earlier.
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.