Guppy : a GPU-like soft-core processor
The popularity of GPU programming languages that explicitly express thread-level parallelism leads to the question of whether they can also be used for programming reconfigurable accelerators. This paper describes Guppy, a GPU-like softcore processor based on the in-order LEON3 core. Our long-term v...
Saved in:
Main Authors: | , , , |
---|---|
Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/98391 http://hdl.handle.net/10220/16260 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-98391 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-983912020-05-28T07:17:50Z Guppy : a GPU-like soft-core processor Hagiescu, Andrei Wong, Weng-Fai Deragisch, Florian Al-Dujaili, Abdullah School of Computer Engineering International Conference on Field-Programmable Technology (2012 : Seoul, Korea) DRNTU::Engineering::Computer science and engineering The popularity of GPU programming languages that explicitly express thread-level parallelism leads to the question of whether they can also be used for programming reconfigurable accelerators. This paper describes Guppy, a GPU-like softcore processor based on the in-order LEON3 core. Our long-term vision is to have a unified programming paradigm for accelerators - regardless of whether they are FPGA or GPU based. While others have explored this from a high level hardware synthesis perspective, we chose to adopt the approach of a parametrically reconfigurable softcore. We will discuss the main architecture features of Guppy, compare its performance to the original core. Our design has been synthesized on a Xilinx Virtex 5 FPGA. 2013-10-04T04:33:31Z 2019-12-06T19:54:45Z 2013-10-04T04:33:31Z 2019-12-06T19:54:45Z 2012 2012 Conference Paper Al Dujaili, A., Deragisch, F., Hagiescu, A., & Wong, W. F. (2012). Guppy : a GPU-like soft-core processor. 2012 International Conference on Field-Programmable Technology (FPT), pp.57-60. https://hdl.handle.net/10356/98391 http://hdl.handle.net/10220/16260 10.1109/FPT.2012.6412112 en |
institution |
Nanyang Technological University |
building |
NTU Library |
country |
Singapore |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Computer science and engineering |
spellingShingle |
DRNTU::Engineering::Computer science and engineering Hagiescu, Andrei Wong, Weng-Fai Deragisch, Florian Al-Dujaili, Abdullah Guppy : a GPU-like soft-core processor |
description |
The popularity of GPU programming languages that explicitly express thread-level parallelism leads to the question of whether they can also be used for programming reconfigurable accelerators. This paper describes Guppy, a GPU-like softcore processor based on the in-order LEON3 core. Our long-term vision is to have a unified programming paradigm for accelerators - regardless of whether they are FPGA or GPU based. While others have explored this from a high level hardware synthesis perspective, we chose to adopt the approach of a parametrically reconfigurable softcore. We will discuss the main architecture features of Guppy, compare its performance to the original core. Our design has been synthesized on a Xilinx Virtex 5 FPGA. |
author2 |
School of Computer Engineering |
author_facet |
School of Computer Engineering Hagiescu, Andrei Wong, Weng-Fai Deragisch, Florian Al-Dujaili, Abdullah |
format |
Conference or Workshop Item |
author |
Hagiescu, Andrei Wong, Weng-Fai Deragisch, Florian Al-Dujaili, Abdullah |
author_sort |
Hagiescu, Andrei |
title |
Guppy : a GPU-like soft-core processor |
title_short |
Guppy : a GPU-like soft-core processor |
title_full |
Guppy : a GPU-like soft-core processor |
title_fullStr |
Guppy : a GPU-like soft-core processor |
title_full_unstemmed |
Guppy : a GPU-like soft-core processor |
title_sort |
guppy : a gpu-like soft-core processor |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/98391 http://hdl.handle.net/10220/16260 |
_version_ |
1681059143054524416 |