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Aniruddha Marathe
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2020 – today
- 2024
- [c22]Banooqa H. Banday, Tanzima Z. Islam, Aniruddha Marathe:
PERFGEN: A Synthesis and Evaluation Framework for Performance Data using Generative AI. COMPSAC 2024: 188-197 - [c21]Gabin Schieffer, Daniel Araújo de Medeiros, Jennifer Faj, Aniruddha Marathe, Ivy Peng:
On the Rise of AMD Matrix Cores: Performance, Power Efficiency, and Programmability. ISPASS 2024: 132-143 - [c20]Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele:
HPC-Coder: Modeling Parallel Programs using Large Language Models. ISC 2024: 1-12 - [i4]Daniel Nichols, Pranav Polasam, Harshitha Menon, Aniruddha Marathe, Todd Gamblin, Abhinav Bhatele:
Performance-Aligned LLMs for Generating Fast Code. CoRR abs/2404.18864 (2024) - [i3]Tanzima Z. Islam, Aniruddha Marathe, Holland Schutte, Mohammad Zaeed:
Data-Driven Analysis to Understand GPU Hardware Resource Usage of Optimizations. CoRR abs/2408.10143 (2024) - 2023
- [c19]Kyle Fan
, Barry Rountree
msr-genie: Navigating Model Specific Registers Across Processor Generations. SC Workshops 2023: 696-703 - [i2]Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele:
Modeling Parallel Programs using Large Language Models. CoRR abs/2306.17281 (2023) - 2022
- [c18]Holland Schutte, Chase Phelps, Aniruddha Marathe
LIBNVCD: An Extendable and User-friendly Multi-GPU Performance Measurement Tool. COMPSAC 2022: 73-82 - [c17]Daniel Nichols
Resource Utilization Aware Job Scheduling to Mitigate Performance Variability. IPDPS 2022: 335-345 - 2021
- [c16]Daniel Curtis Wilson, Siddhartha Jana, Aniruddha Marathe
Introducing Application Awareness Into a Unified Power Management Stack. IPDPS 2021: 320-329 - 2020
- [j5]Nirmal Kumbhare, Ali Akoglu
Dynamic power management for value-oriented schedulers in power-constrained HPC system. Parallel Comput. 99: 102686 (2020) - [j4]Nirmal Kumbhare
A Value-Oriented Job Scheduling Approach for Power-Constrained and Oversubscribed HPC Systems. IEEE Trans. Parallel Distributed Syst. 31(6): 1419-1433 (2020) - [c15]Xingfu Wu
Toward an End-to-End Auto-tuning Framework in HPC PowerStack. CLUSTER 2020: 473-483 - [i1]Xingfu Wu, Aniruddha Marathe, Siddhartha Jana, Ondrej Vysocky, Jophin John, Andrea Bartolini, Lubomir Riha, Michael Gerndt, Valerie Taylor, Sridutt Bhalachandra:
Toward an End-to-End Auto-tuning Framework in HPC PowerStack. CoRR abs/2008.06571 (2020)
2010 – 2019
- 2019
- [c14]Nirmal Kumbhare, Aniruddha Marathe
Adaptive Power Reallocation for Value-Oriented Schedulers in Power-Constrained HPC. PDCAT 2019: 133-139 - 2018
- [c13]Neha Gholkar, Frank Mueller, Barry Rountree, Aniruddha Marathe
PShifter: feedback-based dynamic power shifting within HPC jobs for performance. HPDC 2018: 106-117 - [c12]Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giménez, Rahul Sridhar, Aniruddha Marathe
Bootstrapping Parameter Space Exploration for Fast Tuning. ICS 2018: 385-395 - 2017
- [c11]Aniruddha Marathe
Towards a Unified Monitoring Framework for Power, Performance and Thermal Metrics: A Case Study on the Evaluation of HPC Cooling Systems. IPDPS Workshops 2017: 974-983 - [c10]Will Whiteside, Shelby H. Funk, Aniruddha Marathe
PANN: Power Allocation via Neural Networks Dynamic Bounded-Power Allocation in High Performance Computing. E2SC@SC 2017: 8:1-8:7 - [c9]Aniruddha Marathe
An empirical survey of performance and energy efficiency variation on Intel processors. E2SC@SC 2017: 9:1-9:8 - [c8]Aniruddha Marathe
Performance modeling under resource constraints using deep transfer learning. SC 2017: 31 - [c7]Alfredo Giménez, Todd Gamblin, Abhinav Bhatele, Chad Wood, Kathleen Shoga, Aniruddha Marathe
ScrubJay: deriving knowledge from the disarray of HPC performance data. SC 2017: 35 - 2016
- [j3]Shivani Agarwal
Exploring the Relationship between Remotely-Sensed Spectral Variables and Attributes of Tropical Forest Vegetation under the Influence of Local Forest Institutions. ISPRS Int. J. Geo Inf. 5(7): 117 (2016) - [j2]Aniruddha Marathe
Exploiting Redundancy and Application Scalability for Cost-Effective, Time-Constrained Execution of HPC Applications on Amazon EC2. IEEE Trans. Parallel Distributed Syst. 27(9): 2574-2588 (2016) - [c6]Aniruddha Marathe
LibPowerMon: A Lightweight Profiling Framework to Profile Program Context and System-Level Metrics. IPDPS Workshops 2016: 1132-1141 - 2015
- [c5]Peter E. Bailey, Aniruddha Marathe
Finding the limits of power-constrained application performance. SC 2015: 79:1-79:12 - [c4]Aniruddha Marathe
A Run-Time System for Power-Constrained HPC Applications. ISC 2015: 394-408 - 2014
- [b1]Aniruddha Marathe:
Evaluation and Optimization of Turnaround Time and Cost of HPC Applications on the Cloud. University of Arizona, Tucson, USA, 2014 - [c3]Aniruddha Marathe
Exploiting redundancy for cost-effective, time-constrained execution of HPC applications on amazon EC2. HPDC 2014: 279-290 - 2013
- [j1]Zheng Gu, Matthew Small, Xin Yuan, Aniruddha Marathe
Protocol Customization for Improving MPI Performance on RDMA-Enabled Clusters. Int. J. Parallel Program. 41(5): 682-703 (2013) - [c2]Aniruddha Marathe, Rachel Harris, David K. Lowenthal, Bronis R. de Supinski, Barry Rountree, Martin Schulz, Xin Yuan:
A comparative study of high-performance computing on the cloud. HPDC 2013: 239-250 - 2011
- [c1]Aniruddha Marathe
Profile Guided MPI Protocol Selection for Point-to-Point Communication Calls. IPDPS Workshops 2011: 733-739
Coauthor Index
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