SYCLOPS
Financiado
Scaling extreme analYtics with Cross-architecture acceLeration based on OPen Sta...
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. Unfortun...
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 RISC-V, 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.
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Duración del proyecto: 35 meses
Fecha Inicio: 2023-01-01
Fecha Fin: 2025-12-31
Fecha Fin: 2025-12-31
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-01-01
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
Presupuesto
El presupuesto total del proyecto asciende a
4M€
Líder del proyecto
EURECOM GIE
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5