In-memory execution of compute kernels using flow-based memristive crossbar computing

Dwaipayan Chakraborty; Sunny Raj; Julio Cesar; Gutierrez Troyle; Thomas Sumit; Kumar Jha

doi:10.1109/ICRC.2017.8123643

In-memory execution of compute kernels using flow-based memristive crossbar computing

Dwaipayan Chakraborty, Sunny Raj, Julio Cesar, Gutierrez Troyle, Thomas Sumit, Kumar Jha

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

8 Scopus citations

Abstract

Rebooting computing using in-memory architectures relies on the ability of emerging devices to execute a legacy software stack. In this paper, we present our approach of executing compute kernels written in a subset of the C programming language using flow-based computing on nanoscale memristor crossbars. Our approach also tests the correctness of the design using the parallel Xyces electronic simulation software. We demonstrate the potential of our approach by designing and testing a compute kernel for edge detection in images.

Original language	English (US)
Title of host publication	2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781538615539
DOIs	https://doi.org/10.1109/ICRC.2017.8123643
State	Published - Nov 28 2017
Externally published	Yes
Event	2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Washington, United States Duration: Nov 8 2017 → Nov 9 2017

Publication series

Name	2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings
Volume	2017-January

Conference

Conference	2017 IEEE International Conference on Rebooting Computing, ICRC 2017
Country/Territory	United States
City	Washington
Period	11/8/17 → 11/9/17

All Science Journal Classification (ASJC) codes

Atomic and Molecular Physics, and Optics
Statistical and Nonlinear Physics
Artificial Intelligence
Computational Theory and Mathematics
Hardware and Architecture
Software

Access to Document

10.1109/ICRC.2017.8123643

Cite this

Chakraborty, D., Raj, S., Cesar, J., Troyle, G., Sumit, T., & Jha, K. (2017). In-memory execution of compute kernels using flow-based memristive crossbar computing. In 2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings (pp. 1-6). (2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRC.2017.8123643

Chakraborty, Dwaipayan ; Raj, Sunny ; Cesar, Julio et al. / In-memory execution of compute kernels using flow-based memristive crossbar computing. 2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-6 (2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings).

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title = "In-memory execution of compute kernels using flow-based memristive crossbar computing",

abstract = "Rebooting computing using in-memory architectures relies on the ability of emerging devices to execute a legacy software stack. In this paper, we present our approach of executing compute kernels written in a subset of the C programming language using flow-based computing on nanoscale memristor crossbars. Our approach also tests the correctness of the design using the parallel Xyces electronic simulation software. We demonstrate the potential of our approach by designing and testing a compute kernel for edge detection in images.",

author = "Dwaipayan Chakraborty and Sunny Raj and Julio Cesar and Gutierrez Troyle and Thomas Sumit and Kumar Jha",

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doi = "10.1109/ICRC.2017.8123643",

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series = "2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings",

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Chakraborty, D, Raj, S, Cesar, J, Troyle, G, Sumit, T & Jha, K 2017, In-memory execution of compute kernels using flow-based memristive crossbar computing. in 2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings. 2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 2017 IEEE International Conference on Rebooting Computing, ICRC 2017, Washington, United States, 11/8/17. https://doi.org/10.1109/ICRC.2017.8123643

In-memory execution of compute kernels using flow-based memristive crossbar computing. / Chakraborty, Dwaipayan; Raj, Sunny; Cesar, Julio et al.
2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-6 (2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings; Vol. 2017-January).

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

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M3 - Conference contribution

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Chakraborty D, Raj S, Cesar J, Troyle G, Sumit T, Jha K. In-memory execution of compute kernels using flow-based memristive crossbar computing. In 2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-6. (2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings). doi: 10.1109/ICRC.2017.8123643

In-memory execution of compute kernels using flow-based memristive crossbar computing

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