Title
Designing Domain-Specific Heterogeneous Architectures From Dataflow Programs
Abstract
The last ten years have seen performance and power requirements pushing computer architectures using only a single core towards so-called manycore systems with hundreds of cores on a single chip. To further increase performance and energy efficiency, we are now seeing the development of heterogeneous architectures with specialized and accelerated cores. However, designing these heterogeneous systems is a challenging task due to their inherent complexity. We proposed an approach for designing domain-specific heterogeneous architectures based on instruction augmentation through the integration of hardware accelerators into simple cores. These hardware accelerators were determined based on their common use among applications within a certain domain. The objective was to generate heterogeneous architectures by integrating many of these accelerated cores and connecting them with a network-on-chip. The proposed approach aimed to ease the design of heterogeneous manycore architectures-and, consequently, exploration of the design space-by automating the design steps. To evaluate our approach, we enhanced our software tool chain with a tool that can generate accelerated cores from dataflow programs. This new tool chain was evaluated with the aid of two use cases: radar signal processing and mobile baseband processing. We could achieve an approximately 4x improvement in performance, while executing complete applications on the augmented cores with a small impact (2.5-13%) on area usage. The generated accelerators are competitive, achieving more than 90% of the performance of hand-written implementations.
Year
DOI
Venue
2018
10.3390/computers7020027
COMPUTERS
Keywords
Field
DocType
heterogeneous architecture design, risc-v, dataflow, QR decomposition, domain-specific processor, accelerator, Autofocus, hardware software co-design
Single-core,RISC-V,Autofocus,Computer science,Parallel computing,Chip,Dataflow,QR decomposition
Journal
Volume
Issue
ISSN
7
2
2073-431X
Citations 
PageRank 
References 
2
0.39
17
Authors
3
Name
Order
Citations
PageRank
Suleyman Savas151.93
Zain ul-Abdin2114.76
Tomas Nordström310515.82