Full Text:   <1252>

Summary:  <1134>

CLC number: TP303

On-line Access: 2022-04-22

Received: 2018-08-22

Revision Accepted: 2018-09-14

Crosschecked: 2018-10-10

Cited: 0

Clicked: 2014

Citations:  Bibtex RefMan EndNote GB/T7714


Ning-hui Sun


-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.10 P.1245-1250


The rise of high-throughput computing

Author(s):  Ning-hui Sun, Yun-gang Bao, Dong-rui Fan

Affiliation(s):  State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing 100080, China

Corresponding email(s):   snh@ict.ac.cn, baoyg@ict.ac.cn, fandr@ict.ac.cn

Key Words:  High-throughput computing, Sysentropy, Information superbahn

Ning-hui Sun, Yun-gang Bao, Dong-rui Fan. The rise of high-throughput computing[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(10): 1245-1250.

@article{title="The rise of high-throughput computing",
author="Ning-hui Sun, Yun-gang Bao, Dong-rui Fan",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T The rise of high-throughput computing
%A Ning-hui Sun
%A Yun-gang Bao
%A Dong-rui Fan
%J Frontiers of Information Technology & Electronic Engineering
%V 19
%N 10
%P 1245-1250
%@ 2095-9184
%D 2018
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1800501

T1 - The rise of high-throughput computing
A1 - Ning-hui Sun
A1 - Yun-gang Bao
A1 - Dong-rui Fan
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 19
IS - 10
SP - 1245
EP - 1250
%@ 2095-9184
Y1 - 2018
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1800501

In recent years, the advent of emerging computing applications, such as cloud computing, artificial intelligence, and the Internet of Things, has led to three common requirements in computer system design: high utilization, high throughput, and low latency. Herein, these are referred to as the requirements of ‘high-throughput computing (HTC)’. We further propose a new indicator called ‘sysentropy’ for measuring the degree of chaos and uncertainty within a computer system. We argue that unlike the designs of traditional computing systems that pursue high performance and low power consumption, HTC should aim at achieving low sysentropy. However, from the perspective of computer architecture, HTC faces two major challenges that relate to (1) the full exploitation of the application’s data parallelism and execution concurrency to achieve high throughput, and (2) the achievement of low latency, even in the cases at which severe contention occurs in data paths with high utilization. To overcome these two challenges, we introduce two techniques: on-chip data flow architecture and labeled von Neumann architecture. We build two prototypes that can achieve high throughput and low latency, thereby significantly reducing sysentropy.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Bao YG, Wang S, 2017. Labeled von Neumann architecture for software-defined cloud. J Comput Sci Technol, 32(2):219-223.

[2]Barroso LA, Clidaras J, Hölzle U, 2013. The Datacenter as a Computer: an Introduction to the Design of Warehouse-Scale Machines (2nd Ed.). Morgan & Claypool Publishers, USA.

[3]Dennis JB, Fosseen JB, Linderman JP, 1974. Data flow schemas. Int Symp on Theoretical Programming, p.187-216.

[4]Fan DR, Li WM, Ye XC, et al., 2018. SmarCo: an efficient many-core processor for high-throughput applications in datacenters. IEEE Int Symp on High Performance Computer Architecture, p.596-607.

[5]Greenberg A, 2015. SDN for the cloud. Keynote of SIGCOMM.

[6]Kapoor R, Porter G, Tewari M, et al., 2012. Chronos: predictable low latency for data center applications. Proc 3rd ACM Symp on Cloud Computing, p.9.

[7]Kasture H, Sanchez D, 2016. Tailbench: a benchmark suite and evaluation methodology for latency-critical applications. IEEE Int Symp on Workload Characterization, p.1-10.

[8]Livny M, 2013. From Principles to Capabilities—the Birth and Evolution of High Throughput Computing. Wisconsin Institutes for Discovery, University of Madison-Wisconsin, USA.

[9]Ma JY, Wang HB, Zhang LX, et al., 2015. Supporting differentiated services in computers via programmable architecture for resourcing-on-demand (PARD). ACM SIGPLAN Not, 50(4):131-143.

[10]Xie Y, 2016. Technology-driven architecture innovation: challenges and opportunities. Proc 43rd ACM/IEEE Int Symp on Computer Architecture, Architecture 2030 Workshop.

[11]Xu ZW, 2012. How much power is needed for a billion-thread high-throughput server? Front Comput Sci, 6(4):339-346.

[12]Xu ZW, Li CD, 2017. Low-entropy cloud computing systems. Sci Sin Inform, 47(9):1149-1163.

[13]Xu ZW, Chi XB, Xiao N, 2016. High-performance computing environment: a review of twenty years of experiments in China. Nat Sci Rev, 3(1):36-48.

[14]Yu Z, 2017. Labeled RISC-V: a new perspective on software-defined architecture. Proc 6th RISC-V} Workshop, p.7.

Open peer comments: Debate/Discuss/Question/Opinion


Please provide your name, email address and a comment

Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2022 Journal of Zhejiang University-SCIENCE