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Tensor Processing Unit (TPU) is an AI accelerator application-specific integrated circuit (ASIC) developed by Google for neural network machine learning, using Google's own TensorFlow software. [2] Google began using TPUs internally in 2015, and in 2018 made them available for third-party use, both as part of its cloud infrastructure and by ...
CPU rendering GPU rendering OpenCL NVIDIA CUDA / OptiX AMD HIP SYCL / Intel DPC++ Apple Metal Texture Streaming (Out-of-Core) V-Ray Yes V-Ray GPU (formerly V-Ray RT) No No No Yes [45] RenderMan Yes No 24 and later [46] No No No ? Arnold Yes No Yes No No No Yes Redshift: No No Yes Redshift for AMD (alpha version) No Yes ? Modo mPath Yes No Yes ...
MLIR (Multi-Level Intermediate Representation) is a unifying software framework for compiler development. [1] MLIR can make optimal use of a variety of computing platforms such as central processing units (CPUs), graphics processing units (GPUs), data processing units (DPUs), Tensor Processing Units (TPUs), field-programmable gate arrays (FPGAs), artificial intelligence (AI) application ...
Google Tensor is a series of ARM64-based system-on-chip (SoC) processors designed by Google for its Pixel devices. It was originally conceptualized in 2016, following the introduction of the first Pixel smartphone, though actual developmental work did not enter full swing until 2020.
Geekbench began as a benchmark for Mac OS X and Windows, [3] and is now a cross-platform benchmark that supports macOS, Windows, Linux, Android and iOS. [4]In version 4, Geekbench started measuring GPU performance in areas such as image processing and computer vision.
In May 2016, Google announced its Tensor processing unit (TPU), an application-specific integrated circuit (ASIC, a hardware chip) built specifically for machine learning and tailored for TensorFlow. A TPU is a programmable AI accelerator designed to provide high throughput of low-precision arithmetic (e.g., 8-bit ), and oriented toward using ...
The official reason for the strategic reset was attributed to delays in hardware and software development. [8] On May 25, 2010, the Technology@Intel blog announced that Larrabee would not be released as a GPU, but instead would be released as a product for high-performance computing competing with the Nvidia Tesla. [9]
Superposition Benchmark is a benchmarking software based on the UNIGINE Engine. The benchmark was developed and published by UNIGINE Company in 2017. The main purpose of software is performance and stability testing for GPUs. Users can choose a workload preset, Low to Extreme, or set the parameters by custom.