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ORCIDViktor K. Prasanna
V. K. Prasanna Kumar
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- affiliation: University of Southern California, Los Angeles, USA
- award (2015): W. Wallace McDowell Award
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2020 – today
- 2020
[j163]Kartik Lakhotia, Rajgopal Kannan, Sourav Pati, Viktor K. Prasanna:
GPOP: A Scalable Cache- and Memory-efficient Framework for Graph Processing over Parts. ACM Trans. Parallel Comput. 7(1): 7:1-7:24 (2020)- [j162]Shijie Zhou, Rajgopal Kannan, Viktor K. Prasanna
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Accelerating Stochastic Gradient Descent Based Matrix Factorization on FPGA. IEEE Trans. Parallel Distrib. Syst. 31(8): 1897-1911 (2020) - [c492]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
Hardware Acceleration of Large Scale GCN Inference. ASAP 2020: 61-68 - [c491]Stéphane Kündig, Constantinos Marios Angelopoulos, Sanmukh R. Kuppannagari, José D. P. Rolim, Viktor K. Prasanna:
Crowdsourced Edge: A Novel Networking Paradigm for the Collaborative Community. DCOSS 2020: 474-481 - [c490]Yuan Meng, Sanmukh R. Kuppannagari, Viktor K. Prasanna:
Accelerating Proximal Policy Optimization on CPU-FPGA Heterogeneous Platforms. FCCM 2020: 19-27 - [c489]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
Accelerating Large Scale GCN Inference on FPGA. FCCM 2020: 241 - [c488]Hanqing Zeng, Viktor K. Prasanna:
GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms. FPGA 2020: 255-265 - [c487]Yue Niu, Rajgopal Kannan, Ajitesh Srivastava, Viktor K. Prasanna:
Reuse Kernels or Activations?: A Flexible Dataflow for Low-latency Spectral CNN Acceleration. FPGA 2020: 266-276 - [c486]Rachit Rajat, Yuan Meng, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Viktor K. Prasanna, Rajgopal Kannan:
QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators. FPGA 2020: 323 - [c485]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
GraphSAINT: Graph Sampling Based Inductive Learning Method. ICLR 2020 - [c484]Yuan Meng, Sanmukh R. Kuppannagari, Rachit Rajat, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators. IPDPS Workshops 2020: 107-114 - [c483]Chung Ming Cheung, Sanmukh Rao Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Load Demand User Profiling in Smart Grids with Distributed Solar Generation. ISGT 2020: 1-5 - [c482]Ajitesh Srivastava, Ta-Yang Wang, Pengmiao Zhang, César Augusto Fonticielha De Rose, Rajgopal Kannan, Viktor K. Prasanna:
MemMAP: Compact and Generalizable Meta-LSTM Models for Memory Access Prediction. PAKDD (2) 2020: 57-68 - [c481]Yang Yang, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
FASTHash: FPGA-Based High Throughput Parallel Hash Table. ISC 2020: 3-22 - [i22]Hanqing Zeng, Viktor K. Prasanna:
GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms. CoRR abs/2001.02498 (2020) - [i21]Ajitesh Srivastava, Naifeng Zhang, Rajgopal Kannan, Viktor K. Prasanna:
Towards High Performance, Portability, and Productivity: Lightweight Augmented Neural Networks for Performance Prediction. CoRR abs/2003.07497 (2020) - [i20]Ajitesh Srivastava, Viktor K. Prasanna:
Learning to Forecast and Forecasting to Learn from the COVID-19 Pandemic. CoRR abs/2004.11372 (2020) - [i19]Ajitesh Srivastava, Viktor K. Prasanna:
Data-driven Identification of Number of Unreported Cases for COVID-19: Bounds and Limitations. CoRR abs/2006.02127 (2020) - [i18]Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K. Prasanna:
Maximum Entropy Model Rollouts: Fast Model Based Policy Optimization without Compounding Errors. CoRR abs/2006.04802 (2020) - [i17]Ajitesh Srivastava, Tianjian Xu, Viktor K. Prasanna:
Fast and Accurate Forecasting of COVID-19 Deaths Using the SIkJα Model. CoRR abs/2007.05180 (2020)
2010 – 2019
- 2019
- [j161]Kartik Lakhotia, Rajgopal Kannan, Qing Dong, Viktor K. Prasanna:
Planting Trees for scalable and efficient Canonical Hub Labeling. Proc. VLDB Endow. 13(4): 492-505 (2019) - [j160]Muhammad Rizwan Saeed, Charalampos Chelmis, Viktor K. Prasanna:
Extracting entity-specific substructures for RDF graph embeddings. Semantic Web 10(6): 1087-1108 (2019) - [j159]Ajitesh Srivastava, Robin Petering, Nicholas Barr, Rajgopal Kannan, Eric Rice, Viktor K. Prasanna:
Network-based intervention strategies to reduce violence among homeless. Soc. Netw. Anal. Min. 9(1): 38:1-38:12 (2019) - [j158]Ranjan Pal, Pan Hui, Viktor K. Prasanna:
Privacy Engineering for the Smart Micro-Grid. IEEE Trans. Knowl. Data Eng. 31(5): 965-980 (2019) - [j157]Shijie Zhou, Rajgopal Kannan, Viktor K. Prasanna, Guna Seetharaman, Qing Wu:
HitGraph: High-throughput Graph Processing Framework on FPGA. IEEE Trans. Parallel Distrib. Syst. 30(10): 2249-2264 (2019) - [c480]Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
RecANt: Network-based Recruitment for Active Fake News Correction. BigData 2019: 940-949 - [c479]Kartik Lakhotia, Rajgopal Kannan, Aditya Gaur, Ajitesh Srivastava, Viktor K. Prasanna:
Parallel edge-based sampling for static and dynamic graphs. CF 2019: 125-134 - [c478]Aggelos Lazaris, Viktor K. Prasanna:
Deep Learning Models For Aggregated Network Traffic Prediction. CNSM 2019: 1-5 - [c477]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Approximate Scheduling of DERs with Discrete Complex Injections. e-Energy 2019: 204-214 - [c476]Chung Ming Cheung, Sanmukh Rao Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Towards Improved Real-Time Observability of Behind-Meter PhotoVoltaic Systems: A Data-Driven Approach. e-Energy 2019: 447-455 - [c475]Rachit Rajat, Hanqing Zeng, Viktor K. Prasanna:
A Flexible Design Automation Tool for Accelerating Quantized Spectral CNNs. FPL 2019: 144-150 - [c474]Chuanxiu Xiong, Ajitesh Srivastava, Rajgopal Kannan, Omkar Damle, Viktor K. Prasanna, Erroll Southers:
On Predicting Crime with Heterogeneous Spatial Patterns: Methods and Evaluation. SIGSPATIAL/GIS 2019: 43-51 - [c473]Yue Niu, Hanqing Zeng, Ajitesh Srivastava, Kartik Lakhotia, Rajgopal Kannan, Yanzhi Wang, Viktor K. Prasanna:
SPEC2: SPECtral SParsE CNN Accelerator on FPGAs. HiPC 2019: 195-204 - [c472]Sanmukh R. Kuppannagari, Rachit Rajat, Rajgopal Kannan, Aravind Dasu, Viktor K. Prasanna:
IP Cores for Graph Kernels on FPGAs. HPEC 2019: 1-7 - [c471]Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware. HPEC 2019: 1-7 - [c470]Aggelos Lazaris, Viktor K. Prasanna:
An LSTM Framework For Modeling Network Traffic. IM 2019: 19-24 - [c469]Chi Zhang, Sanmukh R. Kuppannagari, Chuanxiu Xiong, Rajgopal Kannan, Viktor K. Prasanna:
A cooperative multi-agent deep reinforcement learning framework for real-time residential load scheduling. IoTDI 2019: 59-69 - [c468]Viktor K. Prasanna:
HCW 2019 Keynote Address. IPDPS Workshops 2019: 5 - [c467]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, Efficient and Scalable Graph Embedding. IPDPS 2019: 462-471 - [c466]Ajitesh Srivastava, Angelos Lazaris, Benjamin Brooks, Rajgopal Kannan, Viktor K. Prasanna:
Predicting memory accesses: the road to compact ML-driven prefetcher. MEMSYS 2019: 461-470 - [c465]Akshit Goel, Sanmukh R. Kuppannagari, Yang Yang, Ajitesh Srivastava, Viktor K. Prasanna:
Parallel Totally Induced Edge Sampling on FPGAs. PARCO 2019: 671-680 - [c464]Kartik Lakhotia, Rajgopal Kannan, Sourav Pati, Viktor K. Prasanna:
GPOP: a cache and memory-efficient framework for graph processing over partitions. PPoPP 2019: 393-394 - [c463]Chi Zhang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Building HVAC Scheduling Using Reinforcement Learning via Neural Network Based Model Approximation. BuildSys@SenSys 2019: 287-296 - [i16]Kartik Lakhotia, Qing Dong, Rajgopal Kannan, Viktor K. Prasanna:
Planting Trees for scalable and efficient Canonical Hub Labeling. CoRR abs/1907.00140 (2019) - [i15]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
GraphSAINT: Graph Sampling Based Inductive Learning Method. CoRR abs/1907.04931 (2019) - [i14]Chi Zhang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Building HVAC Scheduling Using Reinforcement Learning via Neural Network Based Model Approximation. CoRR abs/1910.05313 (2019) - [i13]Yue Niu, Hanqing Zeng, Ajitesh Srivastava, Kartik Lakhotia, Rajgopal Kannan, Yanzhi Wang, Viktor K. Prasanna:
SPEC2: SPECtral SParsE CNN Accelerator on FPGAs. CoRR abs/1910.11103 (2019) - 2018
- [j156]Muhammad Rizwan Saeed, Charalampos Chelmis, Viktor K. Prasanna:
ASQFor: Automatic SPARQL query formulation for the non-expert. AI Commun. 31(1): 19-32 (2018) - [j155]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Optimal Discrete Net-Load Balancing in Smart Grids with High PV Penetration. ACM Trans. Sens. Networks 14(3-4): 24:1-24:30 (2018) - [j154]Da Tong, Viktor K. Prasanna:
Sketch Acceleration on FPGA and its Applications in Network Anomaly Detection. IEEE Trans. Parallel Distrib. Syst. 29(4): 929-942 (2018) - [c462]Ajitesh Srivastava, Robin Petering, Rajgopal Kannan, Eric Rice, Viktor K. Prasanna:
How to Stop Violence Among Homeless: Extension of Voter Model and Intervention Strategies. ASONAM 2018: 83-86 - [c461]Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
FActCheck: Keeping Activation of Fake News at Check. AAMAS 2018: 2079-2081 - [c460]Shijie Zhou, Rajgopal Kannan, Hanqing Zeng, Viktor K. Prasanna:
An FPGA framework for edge-centric graph processing. CF 2018: 69-77 - [c459]Hanqing Zeng, Ren Chen, Chi Zhang, Viktor K. Prasanna:
A Framework for Generating High Throughput CNN Implementations on FPGAs. FPGA 2018: 117-126 - [c458]Shijie Zhou, Rajgopal Kannan, Yu Min, Viktor K. Prasanna:
FASTCF: FPGA-based Accelerator for STochastic-Gradient-Descent-based Collaborative Filtering. FPGA 2018: 259-268 - [c457]Qing Dong, Kartik Lakhotia, Hanqing Zeng, Rajgopal Karman, Viktor K. Prasanna, Guna Seetharaman:
A Fast and Efficient Parallel Algorithm for Pruned Landmark Labeling. HPEC 2018: 1-7 - [c456]Jürgen Becker, Viktor K. Prasanna, Markus Weimer, Wayne Luk, Kaveh Aasaraai, Derek Chiou:
RAW 2018 Invited Talks. IPDPS Workshops 2018: 81-82 - [c455]Muhammad Rizwan Saeed, Viktor K. Prasanna:
Extracting Entity-Specific Substructures for RDF Graph Embedding. IRI 2018: 378-385 - [c454]Chung Ming Cheung, Rajgopal Kannan, Viktor K. Prasanna:
Temporal ensemble learning of univariate methods for short term load forecasting. ISGT 2018: 1-5 - [c453]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Risk aware net load balancing in micro grids with high DER penetration. ISGT 2018: 1-5 - [c452]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
NO-LESS: Near optimal curtailment strategy selection for net load balancing in micro grids. ISGT 2018: 1-5 - [c451]Weiyi Sun, Hanqing Zeng, Yi-Hua Edward Yang, Viktor K. Prasanna:
Throughput-Optimized Frequency Domain CNN with Fixed-Point Quantization on FPGA. ReConFig 2018: 1-8 - [c450]Chung Ming Cheung, Wen Zhong, Chuanxiu Xiong, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Behind-the-Meter Solar Generation Disaggregation using Consumer Mixture Models. SmartGridComm 2018: 1-6 - [c449]Chi Zhang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Generative Adversarial Network for Synthetic Time Series Data Generation in Smart Grids. SmartGridComm 2018: 1-6 - [c448]Kartik Lakhotia, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating PageRank using Partition-Centric Processing. USENIX Annual Technical Conference 2018: 427-440 - [i12]Muhammad Rizwan Saeed, Charalampos Chelmis, Viktor K. Prasanna:
Not all Embeddings are created Equal: Extracting Entity-specific Substructures for RDF Graph Embedding. CoRR abs/1804.05184 (2018) - [i11]Kartik Lakhotia, Sourav Pati, Rajgopal Kannan, Viktor K. Prasanna:
GPOP: A cache- and work-efficient framework for Graph Processing Over Partitions. CoRR abs/1806.08092 (2018) - [i10]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, Efficient and Scalable Graph Embedding. CoRR abs/1810.11899 (2018) - 2017
- [j153]Qunzhi Zhou, Yogesh Simmhan, Viktor K. Prasanna:
Knowledge-infused and consistent Complex Event Processing over real-time and persistent streams. Future Gener. Comput. Syst. 76: 391-406 (2017) - [j152]Ranjan Pal, Viktor K. Prasanna:
The STREAM Mechanism for CPS Security The Case of the Smart Grid. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 36(4): 537-550 (2017) - [j151]Ren Chen, Shreyas G. Singapura, Viktor K. Prasanna:
Optimal dynamic data layouts for 2D FFT on 3D memory integrated FPGA. J. Supercomput. 73(2): 652-663 (2017) - [j150]Da Tong, Yun Rock Qu, Viktor K. Prasanna:
Accelerating Decision Tree Based Traffic Classification on FPGA and Multicore Platforms. IEEE Trans. Parallel Distrib. Syst. 28(11): 3046-3059 (2017) - [j149]Ren Chen, Viktor K. Prasanna:
Computer Generation of High Throughput and Memory Efficient Sorting Designs on FPGA. IEEE Trans. Parallel Distrib. Syst. 28(11): 3100-3113 (2017) - [j148]Philip Heng Wai Leong, Hideharu Amano, Jason Helge Anderson, Koen Bertels, João M. P. Cardoso, Oliver Diessel, Guy Gogniat, Mike Hutton, JunKyu Lee, Wayne Luk, Patrick Lysaght, Marco Platzner, Viktor K. Prasanna, Tero Rissa, Cristina Silvano, Hayden Kwok-Hay So, Yu Wang:
The First 25 Years of the FPL Conference: Significant Papers. ACM Trans. Reconfigurable Technol. Syst. 10(2): 15:1-15:17 (2017) - [c447]Abhinav Podili, Chi Zhang, Viktor K. Prasanna:
Fast and efficient implementation of Convolutional Neural Networks on FPGA. ASAP 2017: 11-18 - [c446]Chung Ming Cheung, Palash Goyal, Viktor K. Prasanna, Arash Saber Tehrani:
OReONet: Deep convolutional network for oil reservoir optimization. BigData 2017: 1277-1282 - [c445]Aggelos Lazaris, Viktor K. Prasanna:
DeepFlow: a deep learning framework for software-defined measurement. CAN@CoNEXT 2017: 43-48 - [c444]Michail Misyrlis, Chung Ming Cheung, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Spatio-Temporal Modeling of Criminal Activity. SocialSens@CPSWeek 2017: 3-8 - [c443]Ren Chen, Viktor K. Prasanna:
Optimal Circuits for Parallel Bit Reversal. DAC 2017: 73:1-73:6 - [c442]Chi Zhang, Viktor K. Prasanna:
Frequency Domain Acceleration of Convolutional Neural Networks on CPU-FPGA Shared Memory System. FPGA 2017: 35-44 - [c441]Kartik Lakhotia, Shreyas G. Singapura, Rajgopal Kannan, Viktor K. Prasanna:
ReCALL: Reordered Cache Aware Locality Based Graph Processing. HiPC 2017: 273-282 - [c440]Oded Green, James Fox, Euna Kim, Federico Busato, Nicola Bombieri, Kartik Lakhotia, Shijie Zhou, Shreyas G. Singapura, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna, David A. Bader:
Quickly finding a truss in a haystack. HPEC 2017: 1-7 - [c439]Shreyas G. Singapura, Rajgopal Kannan, Viktor K. Prasanna:
Optimal data layout for block-level random accesses to scratchpad. HPEC 2017: 1-7 - [c438]Shreyas G. Singapura, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
OSCAR: Optimizing SCrAtchpad reuse for graph processing. HPEC 2017: 1-7 - [c437]Shijie Zhou, Kartik Lakhotia, Shreyas G. Singapura, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna, James Fox, Euna Kim, Oded Green, David A. Bader:
Design and implementation of parallel PageRank on multicore platforms. HPEC 2017: 1-6 - [c436]Charith Wickramaarachchi, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
PReSS towards a secure smart grid: Protection recommendations against smart spoofing. ISGT 2017: 1-5 - [c435]Hanqing Zeng, Chi Zhang, Viktor K. Prasanna:
Fast generation of high throughput customized deep learning accelerators on FPGAs. ReConFig 2017: 1-8 - [c434]Shijie Zhou, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating low rank matrix completion on FPGA. ReConFig 2017: 1-7 - [c433]Shijie Zhou, Viktor K. Prasanna:
Accelerating Graph Analytics on CPU-FPGA Heterogeneous Platform. SBAC-PAD 2017: 137-144 - [c432]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Optimal net-load balancing in smart grids with high PV penetration. BuildSys@SenSys 2017: 27:1-27:10 - [p2]Muhammad Rizwan Saeed, Charalampos Chelmis, Viktor K. Prasanna:
Automatic Integration and Querying of Semantic Rich Heterogeneous Data: Laying the Foundations for Semantic Web of Things. Managing the Web of Things 2017: 251-273 - [i9]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Optimal Net-Load Balancing in Smart Grids with High PV Penetration. CoRR abs/1709.00644 (2017) - [i8]Kartik Lakhotia, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating PageRank using Partition-Centric Processing. CoRR abs/1709.07122 (2017) - 2016
- [j147]Om Prasad Patri, Anand V. Panangadan, Vikrambhai S. Sorathia, Viktor K. Prasanna:
Sensors to Events: Semantic Modeling and Recognition of Events from Data Streams. Int. J. Semantic Comput. 10(4): 461-502 (2016) - [j146]Viktor K. Prasanna:
Message from the Editor-in-Chief. J. Parallel Distributed Comput. 87: iii (2016) - [j145]Yun Rock Qu, Viktor K. Prasanna:
Compact hash tables for decision-trees. Parallel Comput. 54: 121-127 (2016) - [j144]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
Computing competing cascades on signed networks. Soc. Netw. Anal. Min. 6(1): 82:1-82:14 (2016) - [j143]Yun Rock Qu, Viktor K. Prasanna:
High-Performance and Dynamically Updatable Packet Classification Engine on FPGA. IEEE Trans. Parallel Distrib. Syst. 27(1): 197-209 (2016) - [j142]Yun Rock Qu, Viktor K. Prasanna:
Fast Online Set Intersection for Network Processing on FPGA. IEEE Trans. Parallel Distrib. Syst. 27(11): 3214-3225 (2016) - [j141]Ranjan Pal, Charalampos Chelmis, Marc Frîncu, Viktor K. Prasanna:
MATCH for the Prosumer Smart Grid The Algorithmics of Real-Time Power Balance. IEEE Trans. Parallel Distrib. Syst. 27(12): 3532-3546 (2016) - [j140]Ranjan Pal, Charalampos Chelmis, Marc Frîncu, Viktor K. Prasanna:
Towards Dynamic Demand Response On Efficient Consumer Grouping Algorithmics. IEEE Trans. Sustain. Comput. 1(1): 20-34 (2016) - [c431]Saima Aman, Charalampos Chelmis, Viktor K. Prasanna:
Learning to REDUCE: A Reduced Electricity Consumption Prediction Ensemble. AAAI Workshop: AI for Smart Grids and Smart Buildings 2016 - [c430]Shreyas G. Singapura, Yi-Hua E. Yang, Anand V. Panangadan, Tamás Németh, Peter Ng, Viktor K. Prasanna:
FPGA-Based Acceleration of Pattern Matching in YARA. ARC 2016: 320-327 - [c429]Charith Wickramaarachchi, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
Distributed exact subgraph matching in small diameter dynamic graphs. BigData 2016: 3360-3369 - [c428]Shijie Zhou, Charalampos Chelmis, Viktor K. Prasanna:
High-Throughput and Energy-Efficient Graph Processing on FPGA. FCCM 2016: 103-110 - [c427]Ren Chen, Viktor K. Prasanna:
Accelerating Equi-Join on a CPU-FPGA Heterogeneous Platform. FCCM 2016: 212-219 - [c426]Greg Harris, Anand V. Panangadan, Viktor K. Prasanna:
GPU-Accelerated Parameter Optimization for Classification Rule Learning. FLAIRS Conference 2016: 436-441 - [c425]Ren Chen, Viktor K. Prasanna:
Optimizing interconnection complexity for realizing fixed permutation in data and signal processing algorithms. FPL 2016: 1-9 - [c424]Shreyas G. Singapura, Rajgopal Kannan, Viktor K. Prasanna:
On-chip memory efficient data layout for 2D FFT on 3D memory integrated FPGA. HPEC 2016: 1-7 - [c423]Sanmukh R. Kuppannagari, Rajgopal Kannan, Charalampos Chelmis, Arash Saber Tehrani, Viktor K. Prasanna:
Optimal Customer Targeting for Sustainable Demand Response in Smart Grids. ICCS 2016: 324-334 - [c422]Sanmukh R. Kuppannagari, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
Implementation of Learning-Based Dynamic Demand Response on a Campus Micro-Grid. IJCAI 2016: 4250-4251 - [c421]Muhammad Rizwan Saeed, Charalampos Chelmis, Viktor K. Prasanna:
Thou Shalt ASQFor and Shalt Receive the Semantic Answer. IJCAI 2016: 4264-4265 - [c420]Chi Zhang, Ren Chen, Viktor K. Prasanna:
High Throughput Large Scale Sorting on a CPU-FPGA Heterogeneous Platform. IPDPS Workshops 2016: 148-155 - [c419]Vasileios Zois, Anand V. Panangadan, Viktor K. Prasanna:
Accelerating Support Count for Association Rule Mining on GPUs. IPDPS Workshops 2016: 1423-1432 - [c418]Greg Harris, Anand V. Panangadan, Viktor K. Prasanna:
PRIMER - A Regression-Rule Learning System for Intervention Optimization. RuleML 2016: 307-321 - [c417]Charalampos Chelmis, Rajgopal Kannan, Viktor K. Prasanna:
Software defined connected prosumer communities. WF-IoT 2016: 684-685 - [c416]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
Mining Large Dense Subgraphs. WWW (Companion Volume) 2016: 111-112 - [i7]Qunzhi Zhou, Yogesh L. Simmhan, Viktor K. Prasanna:
Knowledge-infused and Consistent Complex Event Processing over Real-time and Persistent Streams. CoRR abs/1611.00676 (2016) - 2015
- [j139]Yun Rock Qu, Shijie Zhou, Viktor K. Prasanna:
A Decomposition-Based Approach for Scalable Many-Field Packet Classification on Multi-core Processors. Int. J. Parallel Program. 43(6): 965-987 (2015) - [j138]Da Tong, Viktor K. Prasanna:
High Throughput Sketch Based Online Heavy Hitter Detection on FPGA. SIGARCH Comput. Archit. News 43(4): 70-75 (2015) - [j137]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
The unified model of social influence and its application in influence maximization. Soc. Netw. Anal. Min. 5(1): 66:1-66:15 (2015) - [j136]Alok Gautam Kumbhare, Yogesh L. Simmhan, Marc Frîncu, Viktor K. Prasanna:
Reactive Resource Provisioning Heuristics for Dynamic Dataflows on Cloud Infrastructure. IEEE Trans. Cloud Comput. 3(2): 105-118 (2015) - [j135]Saima Aman, Yogesh L. Simmhan, Viktor K. Prasanna:
Holistic Measures for Evaluating Prediction Models in Smart Grids. IEEE Trans. Knowl. Data Eng. 27(2): 475-488 (2015) - [c415]Saima Aman, Charalampos Chelmis, Viktor K. Prasanna:
Influence-Driven Model for Time Series Prediction from Partial Observations. AAAI 2015: 601-607 - [c414]