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GPU: TeraScale 2 (Evergreen); all A and E series models feature Redwood-class integrated graphics on die (BeaverCreek for the dual-core variants and WinterPark for the quad-core variants). Sempron and Athlon models exclude integrated graphics. [24] List of embedded GPU's; Support for up to four DIMMs of up to DDR3-1866 memory
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.
10.1 11.1 Windows 8+ FL10_1 3.1 Windows 3.3 macOS [25] 3.3 Linux ES 3.0 Linux: No 21.3 1720 No Desktop Celeron G4x0 Celeron G5x0 Celeron G530T Pentium G6xx Pentium G6x0T Pentium G8x0 650–1100 HD Graphics 2000: Desktop: Core i3-2102 Core i3-21x0 Core i3-21x0T Core i5-2xx0 Core i5-2x00S Core i5-2xx0T Core i7-2600 Core i7-2600S: 0102: 650–1350 ...
An Intel Arc A770 16 GB, the highest-end desktop GPU from Intel's first generation Alchemist GPUs, with a Rubik's Cube for scale. Developed under the previous codename "DG2", the first generation of Intel Arc GPUs (codenamed "Alchemist") released on March 30, 2022. [1] [13] It comes in both add-on desktop card and laptop form factors.
ROCm [3] is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains: general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), heterogeneous computing.
6-core ARM Cortex-A78AE v8.2 64-bit CPU 1.5MB L2 + 4MB L3 4–8 GiB 7–10 W 2023 Jetson Orin NX 70–100 TOPS 1024-core Nvidia Ampere architecture GPU with 32 Tensor cores up to 8-core ARM Cortex-A78AE v8.2 64-bit CPU 2MB L2 + 4MB L3 8–16 GiB 10–25 W 2023 Jetson AGX Orin 200-275 TOPS up to 2048-core Nvidia Ampere architecture GPU with 64 ...
Torch is used by the Facebook AI Research Group, [8] IBM, [9] Yandex [10] and the Idiap Research Institute. [11] Torch has been extended for use on Android [12] [better source needed] and iOS. [13] [better source needed] It has been used to build hardware implementations for data flows like those found in neural networks. [14]
TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. [citation needed] Its flexible architecture allows for easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.