Warwick Data Store: A Data Structure Abstraction Library

Richard O. Kirk; Martin Nolten; Robert Kevis; Timothy R. Law; Satheesh Maheswaran; Steven A. Wright; Seimon Powell; Gihan R. Mudalige; Stephen A. Jarvis

doi:10.1109/PMBS51919.2020.00013

Warwick Data Store: A Data Structure Abstraction Library

Richard O. Kirk^*, Martin Nolten, Robert Kevis, Timothy R. Law, Satheesh Maheswaran, Steven A. Wright, Seimon Powell, Gihan R. Mudalige, Stephen A. Jarvis

^*Corresponding author for this work

Engineering and Physical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

With the increasing complexity of memory architectures and scientific applications, developing data structures that are performant, portable, scalable, and support developer productivity, is a challenging task. In this paper, we present Warwick Data Store (WDS), a lightweight and extensible C++ template library designed to manage these complexities and allow rapid prototyping. WDS is designed to abstract details of the underlying data structures away from the user, thus easing application development and optimisation. We show that using WDS does not significantly impact achieved performance across a variety of different scientific benchmarks and proxy-applications, compilers, and different architectures. The overheads are largely below 30% for smaller problems, with the overhead deceasing to below 10% when using larger problems. This shows that the library does not significantly impact the performance, while providing additional functionality to data structures, and the ability to optimise data structures without changing the application code.

Original language	English
Title of host publication	Proceedings of PMBS 2020
Subtitle of host publication	Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	71-85
Number of pages	15
ISBN (Electronic)	9781665422659
DOIs	https://doi.org/10.1109/PMBS51919.2020.00013
Publication status	Published - Nov 2020
Event	2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, PMBS 2020 - Virtual, Atlanta, United States Duration: 12 Nov 2020 → 12 Nov 2020

Publication series

Name	Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference	2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, PMBS 2020
Country/Territory	United States
City	Virtual, Atlanta
Period	12/11/20 → 12/11/20

Bibliographical note

Funding Information:
This work was supported by the UK Atomic Weapons Establishment under grant CDK0724 (AWE TechnicalOutreach Programme). Prof. Stephen Jarvis is an AWE William Penney Fellow. This work would not have been possible without the assistance of a number of members of the Applied Computer Science team at AWE, to whom we would like to express our gratitude.

Funding Information:
Isambard is a UK National Tier-2 HPC Service based at the University of Bristol, operated by GW4 and the UK Met Office, and funded by EPSRC.

Funding Information:
CLX-AP is an Intel development system managed and funded by Intel UK. We are grateful for the support of Dr. Andrew Mallinson at Intel for his comments and guidance.

Publisher Copyright:
© 2020 IEEE.

Keywords

Data Structures
High Performance Computing
Mini-Applications

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Modelling and Simulation
Computer Science (miscellaneous)
Hardware and Architecture

Access to Document

10.1109/PMBS51919.2020.00013

Cite this

Kirk, R. O., Nolten, M., Kevis, R., Law, T. R., Maheswaran, S., Wright, S. A., Powell, S., Mudalige, G. R., & Jarvis, S. A. (2020). Warwick Data Store: A Data Structure Abstraction Library. In Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 71-85). Article 9307883 (Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/PMBS51919.2020.00013

Kirk, Richard O. ; Nolten, Martin ; Kevis, Robert et al. / Warwick Data Store : A Data Structure Abstraction Library. Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers (IEEE), 2020. pp. 71-85 (Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis).

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title = "Warwick Data Store: A Data Structure Abstraction Library",

abstract = "With the increasing complexity of memory architectures and scientific applications, developing data structures that are performant, portable, scalable, and support developer productivity, is a challenging task. In this paper, we present Warwick Data Store (WDS), a lightweight and extensible C++ template library designed to manage these complexities and allow rapid prototyping. WDS is designed to abstract details of the underlying data structures away from the user, thus easing application development and optimisation. We show that using WDS does not significantly impact achieved performance across a variety of different scientific benchmarks and proxy-applications, compilers, and different architectures. The overheads are largely below 30% for smaller problems, with the overhead deceasing to below 10% when using larger problems. This shows that the library does not significantly impact the performance, while providing additional functionality to data structures, and the ability to optimise data structures without changing the application code. ",

keywords = "Data Structures, High Performance Computing, Mini-Applications",

author = "Kirk, {Richard O.} and Martin Nolten and Robert Kevis and Law, {Timothy R.} and Satheesh Maheswaran and Wright, {Steven A.} and Seimon Powell and Mudalige, {Gihan R.} and Jarvis, {Stephen A.}",

note = "Funding Information: This work was supported by the UK Atomic Weapons Establishment under grant CDK0724 (AWE TechnicalOutreach Programme). Prof. Stephen Jarvis is an AWE William Penney Fellow. This work would not have been possible without the assistance of a number of members of the Applied Computer Science team at AWE, to whom we would like to express our gratitude. Funding Information: Isambard is a UK National Tier-2 HPC Service based at the University of Bristol, operated by GW4 and the UK Met Office, and funded by EPSRC. Funding Information: CLX-AP is an Intel development system managed and funded by Intel UK. We are grateful for the support of Dr. Andrew Mallinson at Intel for his comments and guidance. Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, PMBS 2020 ; Conference date: 12-11-2020 Through 12-11-2020",

year = "2020",

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language = "English",

series = "Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis",

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Kirk, RO, Nolten, M, Kevis, R, Law, TR, Maheswaran, S, Wright, SA, Powell, S, Mudalige, GR & Jarvis, SA 2020, Warwick Data Store: A Data Structure Abstraction Library. in Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis., 9307883, Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis, Institute of Electrical and Electronics Engineers (IEEE), pp. 71-85, 2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, PMBS 2020, Virtual, Atlanta, Georgia, United States, 12/11/20. https://doi.org/10.1109/PMBS51919.2020.00013

Warwick Data Store: A Data Structure Abstraction Library. / Kirk, Richard O.; Nolten, Martin; Kevis, Robert et al.
Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers (IEEE), 2020. p. 71-85 9307883 (Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Kirk RO, Nolten M, Kevis R, Law TR, Maheswaran S, Wright SA et al. Warwick Data Store: A Data Structure Abstraction Library. In Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers (IEEE). 2020. p. 71-85. 9307883. (Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis). doi: 10.1109/PMBS51919.2020.00013

Warwick Data Store: A Data Structure Abstraction Library

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this