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

 ORCID:

Ning-hui Sun

http://orcid.org/0000-0002-4179-2660

-   Go to

Article info.
Open peer comments

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

http://doi.org/10.1631/FITEE.1800501


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",
volume="19",
number="10",
pages="1245-1250",
year="2018",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1800501"
}

%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

TY - JOUR
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


Abstract: 
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.

高通量计算的兴起

摘要:近年来,云计算、人工智能和物联网等新兴计算应用的出现,对计算机系统设计提出3个共同要求:高利用率、高吞吐量和低延迟。在这里,这些被称为"高通量计算"的要求。我们进一步提出一种新指标,称为"系统熵",用于测量计算机系统的混乱程度和不确定性。我们认为,与追求高性能和低功耗的传统计算系统的设计不同,高通量计算应致力于实现低并发性。然而,从计算机体系结构角度看,高通量计算面临两大挑战:(1)如何充分利用应用程序数据的并行和并发执行来实现高吞吐量;(2)如何获得低延迟,即便在具有高利用率的数据路径中发生严重争用的情况下。为应对这两个挑战,引入两种技术:片上数据流体系结构和标签化冯诺依曼体系结构。构建了两个可以实现高吞吐量和低延迟的原型,显著降低了系统熵。

关键词:高通量计算;系统熵;信息高铁

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

Reference

[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

<1>

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