Programming is supported in OpenCL and Python, in addition to supporting the compilation of CUDA through AMD's Heterogeneous-compute Interface for Portability and Heterogeneous Compute Compiler. It supports the deep learning frameworks: Theano, Caffe, TensorFlow, MXNet, Microsoft Cognitive Toolkit, Torch, and Chainer. This is intended to compete with the deep learning portions of Nvidia's CUDA library. Much of this extends the GPUOpen's Boltzmann Initiative software. MIOpen is AMD's deep learning library to enable GPU acceleration of deep learning. The MI6, MI8, and MI25 products all support AMD's MxGPU virtualization technology, enabling sharing of GPU resources across multiple users.
#Radeon 7 fp64 software
Acceleratorįollowing software is, as of 2022, regrouped under the Radeon Open Compute meta-project. The MI25 also provides 768 GFLOPS peak double precision (FP64) at 1/16th rate. The MI25 is rated at <300W TDP with passive cooling.
In contrast to the MI6 and MI8, the MI25 is able to increase performance when using lower precision numbers, and accordingly is expected to reach 24.6 TFLOPS when using FP16 numbers. The MI25 performance is expected to be 12.3 TFLOPS using FP32 numbers. The MI25 is a Vega based card, utilizing HBM2 memory. The MI8 has a peak (FP64) double precision compute performance 512 GFLOPS. At 8.2 TFLOPS (FP16 and FP32), the MI8 is marked toward inference. The MI8 has 4 GB of High Bandwidth Memory. The MI8 is a Fiji based card, analogous to the R9 Nano, and expected to have a <175W TDP. The MI6 has a peak double precision (FP64) compute performance of 358 GFLOPS. At 5.7 TFLOPS ( FP16 and FP32), the MI6 is expected to be used primarily for inference, rather than neural network training. The MI6 is a passively cooled, Polaris 10 based card with 16 GB of GDDR5 memory and with a <150 W TDP. The three initial Radeon Instinct products were announced on December 12, 2016, and released on June 20, 2017, with each based on a different architecture. Main articles: List of AMD workstation GPUs and List of AMD mobile workstation GPUs
0 kommentar(er)
