This month is dedicated to the AI Vector Accelerator (AVA) project at Southampton University.
Speakers
Oana Lazar, Kunal Dalal, Adomas Lebedys and Yu Xia, University of Southampton
Agenda
18:00 - Socialize
18:30 - Webinar starts
20:00 - Close
Synopsis
The “Plan B” COVID-19 rules have rather spoilt our arrangements in the short term. However, one week later than originally planned, we are delighted to be able to bring you a purely virtual quarterly meetup for the London open source community, focusing on RISC-V and open source, hosted by the BCS Open Source Specialist Group and the UK Open Source Hardware User Group. These meetings provide an opportunity to share the latest ideas around open source in the RISC-V ecosystem, combined with plenty of time for networking.
This month is dedicated to the AI Vector Accelerator (AVA) project at Southampton University.
This will be a purely virtual meeting. You are invited to join and socialize from 18:00, the main talks will start at 18:30.
There is no requirement to register, you can just connect to the videoconference using BigBlueButton using this link. Thank you to GWDG for providing hosting for this meeting. We are also recording the talks for later posting on our YouTube channel.
The livestream link will be open from 18:00 for networking, and the event will start at 18:30 prompt. We’ll keep the link open afterwards for discussion.
Benchmarking the AI Vector Accelerator (AVA) with CV32E40X using the CV-X-IF
The AVA coprocessor implements a small subset of the RISC-V Vector extension, intended to accelerate AI inference applications. The point is to demonstrate that considerable speedup can be achieved using a minimal instruction set extension (in this case 8 instructions).
The AVA project has created a reference implementation using the Open Hardware Group’s CV32E40X core. This implementation is particularly notable for being the first use of the Open Hardware Group’s X-Interface, designed to make the creation of custom instruction set extensions as simple as possible. The benefit is measured using the TinyMLPerf benchmarking suite.
In this talk and discussion, the team will present the work to date, the challenges they faced, and the results they have achieved as part of this Master’s project sponsored by Embecosm.
About the speakers
Oana Lazar is in her fifth and final year studying MEng Electronic Engineering at the University of Southampton. During her fourth year, she completed a 12-month UKESF industrial placement with Tessent Embedded Analytics (formerly UltraSoC and now a Siemens Company) working on the Secure-CAV project. Her interests include embedded software for security applications, cybersecurity, and machine learning. She was recently named the 2021 UKESF Scholar of the Year.
Yu Xia is a final year MEng Electronic Engineering student at the University of Southampton studying modules focused on computer systems and VLSI design. Yu’s interests are within RTL design and verification for RISC computer architectures, previously interning at Arm as part of his UKESF scholarship scheme. He will be joining Arm in September as a graduate systems engineer.
Kunal Dalal is in the final year of his MEng in Electronic Engineering at the University of Southampton. Alongside his part-time role in Application Engineering at Arm as an undergraduate, he is undertaking research with members of the POETS project at the University of Southampton. Kunal’s interests lie in the RTL design of different accelerator microarchitectures, and the deployment of heterogeneous architectures in general.
Adomas Lebedys is in the final year of his MEng degree in Electrical and Electronic Engineering at the University of Southampton, with interests in systems programming, computer architecture, and machine learning. Outside his course, he leads the design of automotive electronics and embedded software for the Southampton University Formula Student Team’s electric vehicle.
This event is brought to you by: BCS Open source specialist group
