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Home » AMD unveils Radeon Instinct MI60 and MI50 7nm Datacenter GPUs

AMD unveils Radeon Instinct MI60 and MI50 7nm Datacenter GPUs

AMD has unveiled the world’s first 7nm datacenter GPUs designed for next-generation deep learning, HPC, cloud computing and rendering applications, the AMD Radeon Instinct MI60 and MI50 accelerators.

The new AMD Radeon Instinct MI60 and MI50 accelerators were designed to efficiently process workloads such as rapidly training complex neural networks, delivering higher levels of floating-point performance, greater efficiencies and new features for datacenter and departmental deployments.

In addition, the accelerators provide ultra-fast floating-point performance and hyper-fast HBM2 (second-generation High-Bandwidth Memory) with up to 1TB/s memory bandwidth speeds. They are also the first GPUs capable of supporting next-generation PCIe 4.02 interconnect, which is up to 2X faster than other x86 CPU-to-GPU interconnect technologies, and feature AMD Infinity Fabric Link GPU interconnect technology that enables GPU-to-GPU communications that are up to 6X faster than PCIe Gen 3 interconnect speeds.

“Legacy GPU architectures limit IT managers from effectively addressing the constantly evolving demands of processing and analyzing huge datasets for modern cloud datacenter workloads,” said David Wang, senior vice president of engineering, Radeon Technologies Group at AMD. “Combining world-class performance and a flexible architecture with a robust software platform and the industry’s leading-edge ROCm open software ecosystem, the new AMD Radeon Instinct accelerators provide the critical components needed to solve the most difficult cloud computing challenges today and into the future.”

The AMD Radeon Instinct MI60 accelerator is expected to ship to datacenter customers by the end of 2018. The AMD Radeon Instinct MI50 accelerator is expected to begin shipping to data center customers by the end of Q1 2019.

source: AMD

Diangson Louie
Diangson Louie
This article was written by Louie Diangson, Managing Editor of YugaTech. You can follow him at @John_Louie.

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