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---
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contributor: max
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date: '2025-02-02T12:11:00'
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title: 'Building Tool Chains for RISC-V AI Accelerators'
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external_url: 'https://www.youtube.com/watch?v=DqNWF26A8Io'
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type: presentation
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tags:
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- oneapi
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- risc-v
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featuring:
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- name: Jeremy Bennett
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affiliation_at_video_production_time: Embecosm
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---
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Building Tool Chains for RISC-V AI Accelerators - Jeremy Bennett, Embecosm
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Our client is developing a massively parallel 64-bit chip for AI inference workloads.
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To facilitate early software development, we are bringing up an AI tool flow for this
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chip in a QEMU RISC-V environment. In this talk, we'll share our experience of getting
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three key AI frameworks working with RISC-V QEMU: Pytorch, Tensorflow and the OpenXLA
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compiler. Our talk will share our experience addressing two key issues. We will describe
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the challenges we faced, their solutions and reflect on the lessons learned for future work.
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The first of these is simply getting the tools to effectively run in an emulated
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RISC-V environment. These tools are large, fast moving pieces of software with extensive
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external dependencies. Our second challenge is performance. AI workloads are inherently
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parallel, and hence run efficiently on vector enabled hardware. However RISC-V vector (RVV)
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is relatively new, and we experienced difficulty getting the performance we expected
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out of the tool flow. At the end of this talk, we hope our audience will have a better
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understanding of the challenges in bringing up an AI tool flow under QEMU. We hope our
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experience will help them bring up their own AI tool flows.

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