ARAPrototyper: Enabling Rapid Prototyping and Evaluation for Accelerator-Rich Architectures

10/31/2016
by   Yu-Ting Chen, et al.
0

Compared to conventional general-purpose processors, accelerator-rich architectures (ARAs) can provide orders-of-magnitude performance and energy gains and are emerging as one of the most promising solutions in the age of dark silicon. However, many design issues related to the complex interaction between general-purpose cores, accelerators, customized on-chip interconnects, and memory systems remain unclear and difficult to evaluate. In this paper we design and implement the ARAPrototyper to enable rapid design space explorations for ARAs in real silicons and reduce the tedious prototyping efforts far down to manageable efforts. First, ARAPrototyper provides a reusable baseline prototype with a highly customizable memory system, including interconnect between accelerators and buffers, interconnect between buffers and last-level cache (LLC) or DRAM, coherency choice at LLC or DRAM, and address translation support. Second, ARAPrototyper provides a clean interface to quickly integrate users' own accelerators written in high-level synthesis (HLS) code. The whole design flow is highly automated to generate a prototype of ARA on an FPGA system-on-chip (SoC). Third, to quickly develop applications that run seamlessly on the ARA prototype, ARAPrototyper provides a system software stack, abstracts the accelerators as software libraries, and provides APIs for software developers. Our experimental results demonstrate that ARAPrototyper enables a wide range of design space explorations for ARAs at manageable prototyping efforts, which has 4,000X to 10,000X faster evaluation time than full-system simulations. We believe that ARAPrototyper can be an attractive alternative for ARA design and evaluation.

READ FULL TEXT

page 4

page 5

page 8

research
09/22/2021

Sextans: A Streaming Accelerator for General-Purpose Sparse-Matrix Dense-Matrix Multiplication

Sparse-Matrix Dense-Matrix multiplication (SpMM) is the key operator for...
research
03/20/2019

Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype

Advances in neuroscience uncover the mechanisms employed by the brain to...
research
09/03/2020

Scalable Light-Weight Integration of FPGA Based Accelerators with Chip Multi-Processors

Modern multicore systems are migrating from homogeneous systems to heter...
research
05/17/2021

MetaSys: A Practical Open-Source Metadata Management System to Implement and Evaluate Cross-Layer Optimizations

This paper introduces the first open-source FPGA-based infrastructure, M...
research
01/08/2023

A Multi-Site Accelerator-Rich Processing Fabric for Scalable Brain-Computer Interfacing

Hull is an accelerator-rich distributed implantable Brain-Computer Inter...
research
01/27/2022

On the RTL Implementation of FINN Matrix Vector Compute Unit

FPGA-based accelerators are becoming more popular for deep neural networ...
research
09/30/2020

AutoDSE: Enabling Software Programmers Design Efficient FPGA Accelerators

Adopting FPGA as an accelerator in datacenters is becoming mainstream fo...

Please sign up or login with your details

Forgot password? Click here to reset