Leveraging RISC-V for AI and Machine Learning

December 13, 2017 //By William Wong, ElectronicDesign
Leveraging RISC-V for AI and Machine Learning
In an attempt to achieve the best TFLOPS per watt for machine learning, Esperanto Technologies is adopting RISC-V in its latest processors.

It’s a work in progress, but  Esperanto Technologies  is looking to use RISC-V technology in  artificial-intelligence (AI) and machine-learning (ML) applications . These days, ML, which is a branch of AI, means  deep neural networks (DNNs) . That, in turn, requires high-performance computing tailored for processing these types of networks.

Esperanto is developing the ET-Maxion and ET-Minion RISC-V processors to address this growing niche, which up to now has been dominated by GPGPUs and  custom hardware designs . Also part of the mix is the ET-Graphics core that targets graphics solutions.

It’s a work in progress, but  Esperanto Technologies  is looking to use RISC-V technology in  artificial-intelligence (AI) and machine-learning (ML) applications . These days, ML, which is a branch of AI, means  deep neural networks (DNNs) . That, in turn, requires high-performance computing tailored for processing these types of networks.

Esperanto is developing the ET-Maxion and ET-Minion RISC-V processors to address this growing niche, which up to now has been dominated by GPGPUs and  custom hardware designs . Also part of the mix is the ET-Graphics core that targets graphics solutions.

The company’s goal is to have the best teraFLOPS per watt using RISC-V for ML. It will do so using RISC-V Domain Specific Extensions (DSEs), including a RISC-V Vector ISA, Tensor instructions, and additional hardware acceleration. One advantage of RISC-V is that it doesn’t use the entire instruction space, making DSEs possible. Of course, one implementation with a DSE may differ from another, so applications would not necessarily be portable unless they were limited to the common RISC-V subset.

Esperanto is aiming for  TSMC 7-nm silicon . The ET-Maxion core is initially based on the open-source,  Berkeley Out-of-Order (BOOM) RISC-V processor  architecture, although Esperanto plans on significant extensions. The company will continue to manage and support the open-source BOOM repository, but the advanced version will be part of the licensable technology.

 

The ET-Maxion starts with the 64-bit RISC-V


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