Neha Gholkar

Works (4)

Updated: July 5th, 2023 15:37

2019 article

Uncore Power Scavenger: A Runtime for Uncore Power Conservation on HPC Systems

PROCEEDINGS OF SC19: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS.

By: N. Gholkar n, F. Mueller n & B. Rountree *

author keywords: high-performance computing; power awareness
TL;DR: This work proposes Uncore Power Scavenger, a runtime system that dynamically detects phase changes and automatically sets the best uncore frequency for every phase to save power without significant impact on performance and achieves up to 20% speedup and proportional energy savings compared to Intel's RAPL with equivalent power usage. (via Semantic Scholar)
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7. Affordable and Clean Energy (OpenAlex)
Source: Web Of Science
Added: July 20, 2020

2018 article

PShiter: Feedback-based Dynamic Power Shiting within HPC Jobs for Performance

HPDC '18: PROCEEDINGS OF THE 27TH INTERNATIONAL SYMPOSIUM ON HIGH-PERFORMANCE PARALLEL AND DISTRIBUTED COMPUTING, pp. 106–117.

By: N. Gholkar n, F. Mueller n, B. Rountree * & A. Marathe *

TL;DR: To the best of the knowledge, PShifter is the first approach to transparently and automatically apply power capping non-uniformly across processors of a job in a dynamic manner adapting to phase changes. (via Semantic Scholar)
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7. Affordable and Clean Energy (OpenAlex)
Source: Web Of Science
Added: April 2, 2019

2016 article

A Power-aware Cost Model for HPC Procurement

2016 IEEE 30TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW), pp. 1110–1113.

By: N. Gholkar n, F. Mueller n & B. Rountree *

TL;DR: This work contributes a procurement model to aid in the design of a capability system that achieves maximum performance while considering manufacturing variations, and appropriately partitions a single, compound system budget into the CAPEX (infrastructure cost) and the OPEX (operating power cost). (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

2016 conference paper

Sensitivity analysis for a quantum informed ferroelectric energy model

Proceedings of the asme conference on smart materials adaptive.

By: L. Leon  n, R. Smith  n, W. Oates * & P. Miles *

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7. Affordable and Clean Energy (OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018

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