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2020 – today
- 2023
- [c61]Octavi Obiols-Sales
, Abhinav Vishnu
, Nicholas Malaya
, Aparna Chandramowlishwaran
:
ADARNet: Deep Learning Predicts Adaptive Mesh Refinement. ICPP 2023: 524-534 - [c60]Gabriel H. Loh
, Michael J. Schulte
, Mike Ignatowski, Vignesh Adhinarayanan, Shaizeen Aga, Derrick Aguren, Varun Agrawal
, Ashwin M. Aji, Johnathan Alsop
, Paul T. Bauman
, Bradford M. Beckmann, Majed Valad Beigi, Sergey Blagodurov, Travis Boraten, Michael Boyer, William C. Brantley, Noel Chalmers, Shaoming Chen, Kevin Cheng, Michael L. Chu, David Cownie, Nicholas Curtis, Joris Del Pino, Nam Duong, Alexandru Dutu, Yasuko Eckert, Christopher Erb, Chip Freitag, Joseph L. Greathouse, Sudhanva Gurumurthi, Anthony Gutierrez, Khaled Hamidouche, Sachin Hossamani, Wei Huang, Mahzabeen Islam, Nuwan Jayasena, John Kalamatianos, Onur Kayiran, Jagadish Kotra, Alan Lee, Daniel Lowell, Niti Madan, Abhinandan Majumdar, Nicholas Malaya, Srilatha Manne, Susumu Mashimo, Damon McDougall
, Elliot Mednick, Michael Mishkin, Mark Nutter, Indrani Paul, Matthew Poremba, Brandon Potter, Kishore Punniyamurthy, Sooraj Puthoor, Steven E. Raasch, Karthik Rao, Gregory Rodgers, Marko Scrbak, Mohammad Seyedzadeh, John Slice, Vilas Sridharan, René van Oostrum, Eric Van Tassell, Abhinav Vishnu, Samuel Wasmundt, Mark Wilkening, Noah Wolfe, Mark Wyse
, Adithya Yalavarti, Dmitri Yudanov:
A Research Retrospective on AMD's Exascale Computing Journey. ISCA 2023: 81:1-81:14 - 2022
- [i20]Octavi Obiols-Sales, Abhinav Vishnu, Nicholas Malaya, Aparna Chandramowlishwaran:
NUNet: Deep Learning for Non-Uniform Super-Resolution of Turbulent Flows. CoRR abs/2203.14154 (2022) - 2021
- [c59]Octavi Obiols-Sales, Abhinav Vishnu, Nicholas Malaya, Aparna Chandramowlishwaran
:
SURFNet: Super-Resolution of Turbulent Flows with Transfer Learning using Small Datasets. PACT 2021: 331-344 - [c58]Sarunya Pumma, Abhinav Vishnu:
Semantic-Aware Lossless Data Compression for Deep Learning Recommendation Model (DLRM). MLHPC@SC 2021: 1-8 - [i19]Octavi Obiols-Sales, Abhinav Vishnu, Nicholas Malaya, Aparna Chandramowlishwaran:
SURFNet: Super-resolution of Turbulent Flows with Transfer Learning using Small Datasets. CoRR abs/2108.07667 (2021) - 2020
- [j25]Nitin A. Gawande
, Jeff A. Daily
, Charles Siegel, Nathan R. Tallent, Abhinav Vishnu:
Scaling Deep Learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing. Future Gener. Comput. Syst. 108: 1162-1172 (2020) - [c57]Octavi Obiols-Sales, Abhinav Vishnu, Nicholas Malaya, Aparna Chandramowlishwaran:
CFDNet: a deep learning-based accelerator for fluid simulations. ICS 2020: 3:1-3:12 - [i18]Octavi Obiols-Sales, Abhinav Vishnu, Nicholas Malaya, Aparna Chandramowlishwaran:
CFDNet: a deep learning-based accelerator for fluid simulations. CoRR abs/2005.04485 (2020)
2010 – 2019
- 2019
- [j24]Abhinav Vishnu, Pavan Balaji, Yong Chen
:
Guest Editor's Introduction: P2S2: SI 2016. Parallel Comput. 82: 1-2 (2019) - [j23]Pavan Balaji, Abhinav Vishnu, Yong Chen
:
Foreword to the special issue for the Workshop on Parallel Programming Models and Systems Software for High-End Computing (P2S2 2017). Parallel Comput. 83: 1-2 (2019) - [j22]Min Si, Abhinav Vishnu, Yong Chen
:
Parallel programming models and systems software for high-end computing (P2S2 2018). Parallel Comput. 89 (2019) - [c56]Thaleia Dimitra Doudali
, Sergey Blagodurov, Abhinav Vishnu, Sudhanva Gurumurthi, Ada Gavrilovska:
Kleio: A Hybrid Memory Page Scheduler with Machine Intelligence. HPDC 2019: 37-48 - 2018
- [j21]Jiankai Sun
, Abhinav Vishnu, Aniket Chakrabarti, Charles Siegel, Srinivasan Parthasarathy
:
ColdRoute: effective routing of cold questions in stack exchange sites. Data Min. Knowl. Discov. 32(5): 1339-1367 (2018) - [j20]Probir Roy
, Shuaiwen Leon Song, Sriram Krishnamoorthy, Abhinav Vishnu, Dipanjan Sengupta, Xu Liu:
NUMA-Caffe: NUMA-Aware Deep Learning Neural Networks. ACM Trans. Archit. Code Optim. 15(2): 24:1-24:26 (2018) - [c55]Anwesha Das, Frank Mueller, Charles Siegel, Abhinav Vishnu:
Desh: deep learning for system health prediction of lead times to failure in HPC. HPDC 2018: 40-51 - [c54]Abhinav Vishnu:
ParLearning 2018 Invited Talk 1. IPDPS Workshops 2018: 854 - [c53]Israt Nisa, Charles Siegel, Aravind Sukumaran-Rajam
, Abhinav Vishnu, P. Sadayappan:
Effective Machine Learning Based Format Selection and Performance Modeling for SpMV on GPUs. IPDPS Workshops 2018: 1056-1065 - [c52]Antonino Tumeo, Mahantesh Halappanavar, John Feo, Assefaw Hadish Gebremedhin, Abhinav Vishnu:
Introduction to GraML 2018. IPDPS Workshops 2018: 1166-1167 - [c51]Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan Oken Hodas:
Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction. KDD 2018: 302-310 - [c50]Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan O. Hodas, Nathan A. Baker:
How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions? WACV 2018: 1340-1349 - [i17]Jeff Daily, Abhinav Vishnu, Charles Siegel, Thomas Warfel, Vinay Amatya:
GossipGraD: Scalable Deep Learning using Gossip Communication based Asynchronous Gradient Descent. CoRR abs/1803.05880 (2018) - [i16]Jiankai Sun, Abhinav Vishnu, Aniket Chakrabarti, Charles Siegel, Srinivasan Parthasarathy:
ColdRoute: Effective Routing of Cold Questions in Stack Exchange Sites. CoRR abs/1807.00462 (2018) - [i15]Garrett B. Goh, Khushmeen Sakloth, Charles Siegel, Abhinav Vishnu, Jim Pfaendtner:
Multimodal Deep Neural Networks using Both Engineered and Learned Representations for Biodegradability Prediction. CoRR abs/1808.04456 (2018) - 2017
- [j19]Garrett B. Goh
, Nathan O. Hodas, Abhinav Vishnu:
Deep learning for computational chemistry. J. Comput. Chem. 38(16): 1291-1307 (2017) - [c49]Javier Rubio-Herrero, Vikas Chandan, Charles Siegel, Abhinav Vishnu, Draguna L. Vrabie
:
A Learning Framework for Control-Oriented Modeling of Buildings. ICMLA 2017: 473-478 - [c48]Junqiao Qiu
, Zhijia Zhao, Bo Wu, Abhinav Vishnu, Shuaiwen Leon Song:
Enabling scalability-sensitive speculative parallelization for FSM computations. ICS 2017: 2:1-2:10 - [c47]Ryan D. Friese
, Nathan R. Tallent
, Abhinav Vishnu, Darren J. Kerbyson, Adolfy Hoisie
:
Generating Performance Models for Irregular Applications. IPDPS 2017: 317-326 - [c46]Nitin A. Gawande, Joshua B. Landwehr, Jeff A. Daily, Nathan R. Tallent, Abhinav Vishnu, Darren J. Kerbyson:
Scaling Deep Learning Workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing. IPDPS Workshops 2017: 399-408 - [c45]Vinay Amatya, Abhinav Vishnu, Charles Siegel, Jeff Daily:
What does fault tolerant deep learning need from MPI? EuroMPI/USA 2017: 13:1-13:11 - [c44]Nathan R. Tallent
, Nitin A. Gawande
, Charles Siegel, Abhinav Vishnu, Adolfy Hoisie
:
Evaluating On-Node GPU Interconnects for Deep Learning Workloads. PMBS@SC 2017: 3-21 - [i14]Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu:
Deep Learning for Computational Chemistry. CoRR abs/1701.04503 (2017) - [i13]Abhinav Vishnu, Joseph B. Manzano, Charles Siegel, Jeff Daily:
User-transparent Distributed TensorFlow. CoRR abs/1704.04560 (2017) - [i12]Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan Oken Hodas, Nathan A. Baker:
Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models. CoRR abs/1706.06689 (2017) - [i11]Vinay Amatya, Abhinav Vishnu, Charles Siegel, Jeff Daily:
What does fault tolerant Deep Learning need from MPI? CoRR abs/1709.03316 (2017) - [i10]Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan O. Hodas, Nathan A. Baker:
How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions? CoRR abs/1710.02238 (2017) - [i9]Garrett B. Goh, Nathan O. Hodas, Charles Siegel, Abhinav Vishnu:
SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties. CoRR abs/1712.02034 (2017) - [i8]Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan O. Hodas:
ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction. CoRR abs/1712.02734 (2017) - 2016
- [j18]Abdul Hameed, Alireza Khoshkbarforoushha, Rajiv Ranjan
, Prem Prakash Jayaraman
, Joanna Kolodziej
, Pavan Balaji, Sherali Zeadally, Qutaibah Marwan Malluhi, Nikos Tziritas, Abhinav Vishnu, Samee U. Khan
, Albert Y. Zomaya
:
A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems. Computing 98(7): 751-774 (2016) - [j17]Georg Hager
, Darren J. Kerbyson, Abhinav Vishnu, Gerhard Wellein:
Performance and power for highly parallel systems. Concurr. Comput. Pract. Exp. 28(2): 187-188 (2016) - [j16]Saif Ur Rehman Malik
, Samee U. Khan
, Sam J. Ewen, Nikos Tziritas, Joanna Kolodziej, Albert Y. Zomaya
, Sajjad Ahmad Madani
, Nasro Min-Allah
, Lizhe Wang
, Cheng-Zhong Xu
, Qutaibah M. Malluhi, Johnatan E. Pecero
, Pavan Balaji, Abhinav Vishnu, Rajiv Ranjan
, Sherali Zeadally, Hongxiang Li:
Performance analysis of data intensive cloud systems based on data management and replication: a survey. Distributed Parallel Databases 34(2): 179-215 (2016) - [j15]Pavan Balaji, Abhinav Vishnu, Yong Chen
:
Special Issue on Parallel Programming Models and Systems Software for High-End Computing. Parallel Comput. 51: 1-2 (2016) - [j14]Abhinav Vishnu, Andres Marquez, Dimitrios S. Nikolopoulos
:
Editorial of the Special issue: SI: E2SC. Parallel Comput. 57: 107 (2016) - [c43]Charles Siegel, Jeff Daily, Abhinav Vishnu:
Adaptive neuron apoptosis for accelerating deep learning on large scale systems. IEEE BigData 2016: 753-762 - [c42]Sameh Shohdy, Abhinav Vishnu, Gagan Agrawal:
Fault Tolerant Frequent Pattern Mining. HiPC 2016: 12-21 - [c41]Shuai Zheng, Abhinav Vishnu, Chris H. Q. Ding:
Accelerating Deep Learning with Shrinkage and Recall. ICPADS 2016: 963-970 - [c40]Sameh Shohdy, Abhinav Vishnu, Gagan Agrawal:
Fault Tolerant Support Vector Machines. ICPP 2016: 598-607 - [c39]Abhinav Vishnu, Hubertus Van Dam
, Nathan R. Tallent
, Darren J. Kerbyson, Adolfy Hoisie
:
Fault Modeling of Extreme Scale Applications Using Machine Learning. IPDPS 2016: 222-231 - [i7]Abhinav Vishnu, Charles Siegel, Jeffrey Daily:
Distributed TensorFlow with MPI. CoRR abs/1603.02339 (2016) - [i6]Shuai Zheng, Abhinav Vishnu, Chris H. Q. Ding:
Accelerating Deep Learning with Shrinkage and Recall. CoRR abs/1605.01369 (2016) - [i5]Vivek V. Datla, David Lin, Max M. Louwerse
, Abhinav Vishnu:
A Data-Driven Approach for Semantic Role Labeling from Induced Grammar Structures in Language. CoRR abs/1606.06274 (2016) - [i4]Charles Siegel, Jeff Daily, Abhinav Vishnu:
Adaptive Neuron Apoptosis for Accelerating Deep Learning on Large Scale Systems. CoRR abs/1610.00790 (2016) - [i3]Sameh Shohdy, Abhinav Vishnu, Gagan Agrawal:
Fault Tolerant Frequent Pattern Mining. CoRR abs/1610.05116 (2016) - 2015
- [j13]Jeff Daily
, Ananth Kalyanaraman, Sriram Krishnamoorthy, Abhinav Vishnu:
A work stealing based approach for enabling scalable optimal sequence homology detection. J. Parallel Distributed Comput. 79-80: 132-142 (2015) - [c38]Abhinav Vishnu, Jeyanthi Narasimhan, Lawrence Holder, Darren J. Kerbyson, Adolfy Hoisie
:
Fast and Accurate Support Vector Machines on Large Scale Systems. CLUSTER 2015: 110-119 - [c37]Abhinav Vishnu, Khushbu Agarwal:
Large Scale Frequent Pattern Mining Using MPI One-Sided Model. CLUSTER 2015: 138-147 - [c36]Daniel G. Chavarría-Miranda, Mahantesh Halappanavar, Sriram Krishnamoorthy, Joseph B. Manzano
, Abhinav Vishnu, Adolfy Hoisie
:
On the Impact of Execution Models: A Case Study in Computational Chemistry. IPDPS Workshops 2015: 255-264 - [c35]Jian Lin
, Khaled Hamidouche, Jie Zhang, Xiaoyi Lu, Abhinav Vishnu, Dhabaleswar K. Panda:
Accelerating k-NN Algorithm with Hybrid MPI and OpenSHMEM. OpenSHMEM 2015: 164-177 - [c34]Nathan R. Tallent
, Abhinav Vishnu, Hubertus Van Dam
, Jeff Daily
, Darren J. Kerbyson, Adolfy Hoisie
:
Diagnosing the causes and severity of one-sided message contention. PPoPP 2015: 130-139 - [c33]Akshay Venkatesh, Abhinav Vishnu, Khaled Hamidouche, Nathan R. Tallent
, Dhabaleswar K. Panda, Darren J. Kerbyson, Adolfy Hoisie
:
A case for application-oblivious energy-efficient MPI runtime. SC 2015: 29:1-29:12 - [i2]Vivek V. Datla, Abhinav Vishnu:
Predicting the top and bottom ranks of billboard songs using Machine Learning. CoRR abs/1512.01283 (2015) - 2014
- [j12]Darren J. Kerbyson, Kevin J. Barker
, Abhinav Vishnu, Adolfy Hoisie
:
A performance comparison of current HPC systems: Blue Gene/Q, Cray XE6 and InfiniBand systems. Future Gener. Comput. Syst. 30: 291-304 (2014) - [c32]Jeff Daily
, Abhinav Vishnu, Bruce J. Palmer
, Hubertus Van Dam
, Darren J. Kerbyson:
On the suitability of MPI as a PGAS runtime. HiPC 2014: 1-10 - [c31]Abhinav Vishnu, Yinglong Xia:
ParLearning Introduction and Committees. IPDPS Workshops 2014: 1599-1600 - [i1]Jeyanthi Narasimhan, Abhinav Vishnu, Lawrence Holder, Adolfy Hoisie:
Fast Support Vector Machines Using Parallel Adaptive Shrinking on Distributed Systems. CoRR abs/1406.5161 (2014) - 2013
- [j11]Giorgio Valentini, Walter Lassonde, Samee Ullah Khan
, Nasro Min-Allah
, Sajjad Ahmad Madani
, Juan Li, Limin Zhang, Lizhe Wang
, Nasir Ghani, Joanna Kolodziej
, Hongxiang Li, Albert Y. Zomaya
, Cheng-Zhong Xu
, Pavan Balaji, Abhinav Vishnu, Frédéric Pinel, Johnatan E. Pecero
, Dzmitry Kliazovich, Pascal Bouvry
:
An overview of energy efficiency techniques in cluster computing systems. Clust. Comput. 16(1): 3-15 (2013) - [j10]Hameed Hussain, Saif Ur Rehman Malik
, Abdul Hameed, Samee Ullah Khan
, Gage Bickler, Nasro Min-Allah
, Muhammad Bilal Qureshi, Limin Zhang, Yongji Wang, Nasir Ghani, Joanna Kolodziej
, Albert Y. Zomaya
, Cheng-Zhong Xu
, Pavan Balaji, Abhinav Vishnu, Frédéric Pinel, Johnatan E. Pecero
, Dzmitry Kliazovich, Pascal Bouvry
, Hongxiang Li, Lizhe Wang
, Dan Chen, Ammar Rayes:
A survey on resource allocation in high performance distributed computing systems. Parallel Comput. 39(11): 709-736 (2013) - [j9]Yong Chen
, Pavan Balaji, Abhinav Vishnu:
Special issue on programming models, systems software, and tools for High-End Computing. Parallel Comput. 39(12): 751-752 (2013) - [j8]Abhinav Vishnu, Pavan Balaji, Yong Chen
:
Guest Editors' introduction. J. Supercomput. 63(2): 323-325 (2013) - [j7]Abhinav Vishnu, Shuaiwen Song, Andres Marquez
, Kevin J. Barker
, Darren J. Kerbyson, Kirk W. Cameron
, Pavan Balaji:
Designing energy efficient communication runtime systems: a view from PGAS models. J. Supercomput. 63(3): 691-709 (2013) - [c30]Abhinav Vishnu, Darren J. Kerbyson, Kevin J. Barker
, Hubertus Van Dam
:
Building Scalable PGAS Communication Subsystem on Blue Gene/Q. IPDPS Workshops 2013: 825-833 - 2012
- [c29]Daniel G. Chavarría-Miranda, Sriram Krishnamoorthy, Abhinav Vishnu:
Global Futures: A Multithreaded Execution Model for Global Arrays-based Applications. CCGRID 2012: 393-401 - [c28]Abhinav Vishnu, Jeff Daily
, Bruce J. Palmer
:
Designing scalable PGAS communication subsystems on cray gemini interconnect. HiPC 2012: 1-10 - [c27]Darren J. Kerbyson, Kevin J. Barker
, Abhinav Vishnu, Adolfy Hoisie
:
Comparing the Performance of Blue Gene/Q with Leading Cray XE6 and InfiniBand Systems. ICPADS 2012: 556-563 - 2011
- [j6]Darren J. Kerbyson, Abhinav Vishnu, Kevin J. Barker
, Adolfy Hoisie
:
Codesign Challenges for Exascale Systems: Performance, Power, and Reliability. Computer 44(11): 37-43 (2011) - [j5]Pavan Balaji, Rinku Gupta, Abhinav Vishnu, Peter H. Beckman:
Mapping communication layouts to network hardware characteristics on massive-scale blue gene systems. Comput. Sci. Res. Dev. 26(3-4): 247-256 (2011) - [j4]Pavan Balaji, Abhinav Vishnu:
Special Issue on Programming Models and Systems Software Support for High-End Computing Applications. Int. J. High Perform. Comput. Appl. 25(2): 135-136 (2011) - [j3]Pavan Balaji, Abhinav Vishnu:
Special Issue on Programming Models, Software and Tools for High-End Computing. Int. J. High Perform. Comput. Appl. 25(4): 353-354 (2011) - [c26]Darren J. Kerbyson, Abhinav Vishnu, Kevin J. Barker
:
Energy Templates: Exploiting Application Information to Save Energy. CLUSTER 2011: 225-233 - [c25]Abhinav Vishnu, Monika ten Bruggencate, Ryan Olson:
Evaluating the Potential of Cray Gemini Interconnect for PGAS Communication Runtime Systems. Hot Interconnects 2011: 70-77 - [c24]Shuaiwen Song, Chun-Yi Su, Rong Ge, Abhinav Vishnu, Kirk W. Cameron
:
Iso-Energy-Efficiency: An Approach to Power-Constrained Parallel Computation. IPDPS 2011: 128-139 - [c23]Bruce J. Palmer
, Manojkumar Krishnan, Abhinav Vishnu:
Tutorial Statement. IPDPS 2011: 506 - [c22]Abhinav Vishnu, Manojkumar Krishnan, Pavan Balaji:
Dynamic Time-Variant Connection Management for PGAS Models on InfiniBand. IPDPS Workshops 2011: 740-746 - [c21]James Dinan, Sriram Krishnamoorthy, Pavan Balaji, Jeff R. Hammond
, Manojkumar Krishnan, Vinod Tipparaju, Abhinav Vishnu:
Noncollective Communicator Creation in MPI. EuroMPI 2011: 282-291 - 2010
- [c20]Abhinav Vishnu, Manojkumar Krishnan:
Efficient On-Demand Connection Management Mechanisms with PGAS Models over InfiniBand. CCGRID 2010: 175-184 - [c19]Abhinav Vishnu, Shuaiwen Song, Andres Marquez
, Kevin J. Barker
, Darren J. Kerbyson, Kirk W. Cameron
, Pavan Balaji:
Designing Energy Efficient Communication Runtime Systems for Data Centric Programming Models. GreenCom/CPSCom 2010: 229-236 - [c18]Abhinav Vishnu, Huub J. J. Van Dam
, Wibe de Jong
, Pavan Balaji, Shuaiwen Song:
Fault-tolerant communication runtime support for data-centric programming models. HiPC 2010: 1-9 - [c17]Manojkumar Krishnan, Robert R. Lewis, Abhinav Vishnu:
Scaling Linear Algebra Kernels Using Remote Memory Access. ICPP Workshops 2010: 369-376 - [c16]Krishna Chaitanya Kandalla, Hari Subramoni, Abhinav Vishnu, Dhabaleswar K. Panda:
Designing topology-aware collective communication algorithms for large scale InfiniBand clusters: Case studies with Scatter and Gather. IPDPS Workshops 2010: 1-8
2000 – 2009
- 2009
- [j2]Abhinav Vishnu, Matthew J. Koop, Adam Moody, Amith R. Mamidala, Sundeep Narravula, Dhabaleswar K. Panda:
Topology agnostic hot-spot avoidance with InfiniBand. Concurr. Comput. Pract. Exp. 21(3): 301-319 (2009) - [c15]Abhinav Vishnu, Manojkumar Krishnan, Dhabaleswar K. Panda:
An efficient hardware-software approach to network fault tolerance with InfiniBand. CLUSTER 2009: 1-9 - 2007
- [c14]Abhinav Vishnu, Matthew J. Koop, Adam Moody, Amith R. Mamidala, Sundeep Narravula, Dhabaleswar K. Panda:
Hot-Spot Avoidance With Multi-Pathing Over InfiniBand: An MPI Perspective. CCGRID 2007: 479-486 - [c13]Sundeep Narravula, A. Marnidala, Abhinav Vishnu, Karthikeyan Vaidyanathan, Dhabaleswar K. Panda:
High Performance Distributed Lock Management Services using Network-based Remote Atomic Operations. CCGRID 2007: 583-590 - [c12]Sundeep Narravula, Amith R. Mamidala, Abhinav Vishnu, Gopalakrishnan Santhanaraman, Dhabaleswar K. Panda:
High Performance MPI over iWARP: Early Experiences. ICPP 2007: 46 - [c11]Abhinav Vishnu, Brad Benton, Dhabaleswar K. Panda:
High Performance MPI on IBM 12x InfiniBand Architecture. IPDPS 2007: 1-8 - [c10]Abhinav Vishnu, Amith R. Mamidala, Sundeep Narravula, Dhabaleswar K. Panda:
Automatic Path Migration over InfiniBand: Early Experiences. IPDPS 2007: 1-8 - [c9]Amith R. Mamidala, Sundeep Narravula, Abhinav Vishnu, Gopalakrishnan Santhanaraman, Dhabaleswar K. Panda:
On using connection-oriented vs. connection-less transport for performance and scalability of collective and one-sided operations: trade-offs and impact. PPoPP 2007: 46-54 - 2006
- [c8]Matthew J. Koop, Wei Huang, Abhinav Vishnu, Dhabaleswar K. Panda:
Memory Scalability Evaluation of the Next-Generation Intel Bensley Platform with InfiniBand. Hot Interconnects 2006: 52-60 - [c7]Amith R. Mamidala, Abhinav Vishnu, Dhabaleswar K. Panda:
Efficient Shared Memory and RDMA Based Design for MPI_Allgather over InfiniBand. PVM/MPI 2006: 66-75 - [c6]Abhinav Vishnu, Prachi Gupta, Amith R. Mamidala, Dhabaleswar K. Panda:
Scalable systems software - A software based approach for providing network fault tolerance in clusters with uDAPL interface: MPI level design and performance evaluation. SC 2006: 85 - 2005
- [j1]Jiuxing Liu, Amith R. Mamidala, Abhinav Vishnu, Dhabaleswar K. Panda:
Evaluating InfiniBand Performance with PCI Express. IEEE Micro 25(1): 20-29 (2005) - [c5]Abhinav Vishnu, Gopalakrishnan Santhanaraman, Wei Huang, Hyun-Wook Jin, Dhabaleswar K. Panda:
Supporting MPI-2 One Sided Communication on Multi-rail InfiniBand Clusters: Design Challenges and Performance Benefits. HiPC 2005: 137-147 - [c4]Sayantan Sur, Abhinav Vishnu, Hyun-Wook Jin, Wei Huang, Dhabaleswar K. Panda:
Can Memory-Less Network Adapters Benefit Next-Generation InfiniBand Systems?. Hot Interconnects 2005: 45-50 - [c3]Abhinav Vishnu, Amith R. Mamidala, Hyun-Wook Jin, Dhabaleswar K. Panda:
Performance Modeling of Subnet Management on Fat Tree InfiniBand Networks using OpenSM. IPDPS 2005 - 2004
- [c2]Jiuxing Liu, Amith R. Mamidala, Abhinav Vishnu, Dhabaleswar K. Panda:
Performance evaluation of InfiniBand with PCI Express. Hot Interconnects 2004: 13-19 - [c1]Jiuxing Liu, Abhinav Vishnu, Dhabaleswar K. Panda:
Building Multirail InfiniBand Clusters: MPI-Level Design and Performance Evaluation. SC 2004: 33
Coauthor Index
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last updated on 2024-08-05 21:17 CEST by the dblp team
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