<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/FDF0AAD9-5452-4D72-B8D1-E1CA781B353E" ns1:id="FDF0AAD9-5452-4D72-B8D1-E1CA781B353E"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/0FE01BB2-3B07-48E6-996B-85A03F365950" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/5ED63D78-7FB0-44FA-B257-D985C7D4C647" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/5ED63D78-7FB0-44FA-B257-D985C7D4C647" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2025-12-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/A4F87F69-EBE2-4DB3-9582-5AF8219BF84A" ns1:rel="FUND" ns1:start="2023-01-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10048920</ns2:identifier></ns2:identifiers><ns2:title>Scaling extreme analYtics with Cross-architecture acceleration based on OPen Standards</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>EU-Funded</ns2:grantCategory><ns2:leadFunder>Horizon Europe Guarantee</ns2:leadFunder><ns2:abstractText>The wide-spread adoption of AI and analytics has resulted in a rapidly expanding market for novel hardware accelerators that can provide energy-efficient scaling of training and inference tasks at both the cloud and edge. Unfortunately, all popular solutions AI acceleration solutions today use proprietary, closed hardware—software stacks, leading to a monopolization of the AI acceleration market by a few large industry players. The vision of SYCLOPS project is to enable better solutions for AI/data mining for extremely large and diverse data by democratizing AI acceleration using open standards, and enabling a healthy, competitive, innovation-driven ecosystem for Europe and beyond. This vision relies on the convergence of two important trends in the industry: (i) the standardization and adoption of RISCV, a free, open Instruction Set Architecture (ISA), for AI and analytics acceleration, and (ii) the emergence and growth of SYCL as a cross-vendor, cross-architecture, data parallel programming model for all types of accelerators, including RISC-V. The goal of project SYCLOPS is to bring together these standards for the first time in order to (i) demonstrate ground-breaking advances in performance and scalability of extreme data analytics using a standards-based, fully-open, AI acceleration approach and (ii) enable the development of inter-operable (open and vendor neutral interfaces/APIs), trustworthy (verifiable and standards-based hardware/software), and green (via application-specific processor customization) AI systems. In doing so, we will use the experience gained in SYCLOPS to contribute back to SYCL and RISC-V standards and foster links to respective academic, industrial and innovator communities (RISC-V foundation, EPI, Khronos, ISO C++). Bringing together the two standards enables codesign in both standards, which in turn, will enable a broader AI accelerator design space, and a richer ecosystem of solutions.</ns2:abstractText></ns2:project>