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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 ...
384-core Nvidia Volta architecture GPU with 48 Tensor cores 2 6-core Nvidia Carmel ARMv8.2 64-bit CPU 6MB L2 + 4MB L3 8 GiB 10–20 W 2023 Jetson Orin Nano [21] 34–67 Sparse INT8 TOPS up to 1024-core Nvidia Ampere architecture GPU with 32 Tensor cores — 6-core ARM Cortex-A78AE v8.2 64-bit CPU 1.5MB L2 + 4MB L3 4–8 GiB 7–25 W 2023
Multi-core, multithreading, 4 hardware-based simultaneous threads per core which can't be disabled unlike regular HyperThreading, Time-multiplexed multithreading, 61 cores per chip, 244 threads per chip, 30.5 MB L2 cache, 300 W TDP, Turbo Boost, in-order dual-issue pipelines, coprocessor, Floating-point accelerator, 512-bit wide Vector-FPU
Integrated graphics chip moved from motherboard into the processor. Improved gaming performance; Can access CPU's cache; Each EU has a 128-bit wide FPU that natively executes eight 16-bit or four 32-bit operations per clock cycle. [20] Hierarchical-Z compression and fast Z clear [21]
Core config – The layout of the graphics pipeline, in terms of functional units. Over time the number, type, and variety of functional units in the GPU core has changed significantly; before each section in the list there is an explanation as to what functional units are present in each generation of processors.
CPU Socket Processors Supported Fab FSB/HT Frequency (MHz) Memory PCI-Express SLI PCI USB PATA SATA LAN Sound Graphics GeForce 9300 MCP7A October 2008 LGA 775: Intel Core 2, Pentium Dual-Core, Core-based Celerons: 1333 MHz DDR3-1333 / DDR2-800 dual channel 2.0 20 lanes No 5 Ports 12 Ports Rev 2.0 No 6 Ports 3.0 Gbit/s 1000 Mbit/s HDA: GeForce 9300
The Nvidia Tesla product line competed with AMD's Radeon Instinct and Intel Xeon Phi lines of deep learning and GPU cards. Nvidia retired the Tesla brand in May 2020, reportedly because of potential confusion with the brand of cars. [1] Its new GPUs are branded Nvidia Data Center GPUs [2] as in the Ampere-based A100 GPU. [3]
Before the Coffee Lake architecture, most Xeon and all desktop and mobile Core i3 and i7 supported hyper-threading while only dual-core mobile i5's supported it. Post Coffee Lake, increased core counts meant hyper-threading is not needed for Core i3, as it then replaced the i5 with four physical cores on the desktop platform. Core i7, on the ...