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Ashutosh Pattnaik
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2020 – today
- 2021
- [c12]Weizheng Xu, Ashutosh Pattnaik, Geng Yuan, Yanzhi Wang, Youtao Zhang, Xulong Tang
:
ScaleDNN: Data Movement Aware DNN Training on Multi-GPU. ICCAD 2021: 1-9 - [i1]Anup Sarma, Sonali Singh, Huaipan Jiang, Ashutosh Pattnaik, Asit K. Mishra, Vijaykrishnan Narayanan, Mahmut T. Kandemir, Chita R. Das:
Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs. CoRR abs/2109.07710 (2021) - 2020
- [c11]Sonali Singh, Anup Sarma, Nicholas Jao, Ashutosh Pattnaik, Sen Lu, Kezhou Yang, Abhronil Sengupta, Vijaykrishnan Narayanan
, Chita R. Das:
NEBULA: A Neuromorphic Spin-Based Ultra-Low Power Architecture for SNNs and ANNs. ISCA 2020: 363-376 - [e1]Adwait Jog, Onur Kayiran, Ashutosh Pattnaik:
GPGPU@PPoPP '20: 13th Annual Workshop on General Purpose Processing using Graphics Processing Unit colocated with 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, San Diego, California, USA, February 23, 2020. ACM 2020, ISBN 978-1-4503-7025-7 [contents]
2010 – 2019
- 2019
- [c10]Ashutosh Pattnaik, Xulong Tang
, Onur Kayiran, Adwait Jog, Asit K. Mishra, Mahmut T. Kandemir, Anand Sivasubramaniam, Chita R. Das:
Opportunistic computing in GPU architectures. ISCA 2019: 210-223 - [c9]Anup Sarma, Huaipan Jiang, Ashutosh Pattnaik, Jagadish Kotra, Mahmut Taylan Kandemir, Chita R. Das:
CASH: compiler assisted hardware design for improving DRAM energy efficiency in CNN inference. MEMSYS 2019: 396-407 - [c8]Haibo Zhang, Shulin Zhao, Ashutosh Pattnaik, Mahmut T. Kandemir, Anand Sivasubramaniam, Chita R. Das:
Distilling the Essence of Raw Video to Reduce Memory Usage and Energy at Edge Devices. MICRO 2019: 657-669 - [c7]Xulong Tang
, Ashutosh Pattnaik, Onur Kayiran, Adwait Jog, Mahmut Taylan Kandemir, Chita R. Das:
Quantifying Data Locality in Dynamic Parallelism in GPUs. SIGMETRICS (Abstracts) 2019: 25-26 - 2018
- [j1]Xulong Tang, Ashutosh Pattnaik, Onur Kayiran, Adwait Jog, Mahmut Taylan Kandemir, Chita R. Das:
Quantifying Data Locality in Dynamic Parallelism in GPUs. Proc. ACM Meas. Anal. Comput. Syst. 2(3): 39:1-39:24 (2018) - 2017
- [c6]Xulong Tang
, Ashutosh Pattnaik, Huaipan Jiang, Onur Kayiran, Adwait Jog, Sreepathi Pai
, Mohamed Assem Ibrahim
, Mahmut T. Kandemir, Chita R. Das:
Controlled Kernel Launch for Dynamic Parallelism in GPUs. HPCA 2017: 649-660 - 2016
- [c5]Onur Kayiran, Adwait Jog, Ashutosh Pattnaik, Rachata Ausavarungnirun, Xulong Tang
, Mahmut T. Kandemir, Gabriel H. Loh, Onur Mutlu, Chita R. Das:
μC-States: Fine-grained GPU Datapath Power Management. PACT 2016: 17-30 - [c4]Ashutosh Pattnaik, Xulong Tang
, Adwait Jog, Onur Kayiran, Asit K. Mishra, Mahmut T. Kandemir, Onur Mutlu, Chita R. Das:
Scheduling Techniques for GPU Architectures with Processing-In-Memory Capabilities. PACT 2016: 31-44 - [c3]Vignesh Adhinarayanan
, Indrani Paul, Joseph L. Greathouse, Wei Huang, Ashutosh Pattnaik, Wu-chun Feng:
Measuring and modeling on-chip interconnect power on real hardware. IISWC 2016: 23-33 - [c2]Adwait Jog, Onur Kayiran, Ashutosh Pattnaik, Mahmut T. Kandemir, Onur Mutlu, Ravishankar R. Iyer, Chita R. Das:
Exploiting Core Criticality for Enhanced GPU Performance. SIGMETRICS 2016: 351-363 - 2015
- [c1]Adwait Jog, Onur Kayiran, Tuba Kesten, Ashutosh Pattnaik, Evgeny Bolotin, Niladrish Chatterjee, Stephen W. Keckler, Mahmut T. Kandemir, Chita R. Das:
Anatomy of GPU Memory System for Multi-Application Execution. MEMSYS 2015: 223-234
Coauthor Index
aka: Mahmut Taylan Kandemir
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