AMD previews new HPC hardware at CES 2018
Building on the enthusiasm generated last year with the release of the Ryzen processors, AMD has now released details of its forthcoming roll-out for the next generation of high-performance computing and graphics products during an event in Las Vegas prior to the opening of CES 2018.
In addition to announcing the first desktop Ryzen processors with built-in Radeon Vega Graphics, AMD also detailed the full line up of Ryzen mobile APUs including the new Ryzen PRO and Ryzen 3 models and provided a first look at the performance of its upcoming 12nm 2nd generation Ryzen desktop CPU expected to launch in April.
In terms of graphics hardware, AMD announced the expansion of the ‘Vega’ family with Radeon Vega Mobile and that its first 7nm product is planned to be a Radeon ‘Vega’ GPU specifically built for machine learning applications.
‘We successfully accomplished the ambitious goals we set for ourselves in 2017, re-establishing AMD as a high-performance computing leader with the introduction and ramp of 10 different product families,’ said AMD President and CEO Dr Lisa Su. ‘We are building on this momentum in 2018 as we make our strongest product portfolio of the last decade even stronger with new CPUs and GPUs that bring more features and more performance to a broad set of markets.’
AMD CTO and SVP Mark Papermaster shared updates on AMD's process technology roadmaps for both x86 processors and graphics architectures. Papermaster announced that x86 development would continue with the ‘Zen’ core, currently shipping in Ryzen desktop and mobile processors, is in production at both 14nm and 12nm, with 12nm samples now shipping.
AMD will also be expanding the ‘Vega’ product family in 2018 with the Radeon Vega Mobile GPU for ultrathin notebooks. The first 7nm AMD product, a Radeon ‘Vega’ based GPU built specifically for machine learning applications.
The company will also release a production-level machine learning software environment with AMD's MIOpen libraries supporting common machine learning frameworks like TensorFlow and Caffe on the ROCm Open eCosystem platform.