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ORCIDViktor K. Prasanna
V. K. Prasanna Kumar
Person information
- affiliation: University of Southern California, Los Angeles, USA
- award (2015): W. Wallace McDowell Award
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2020 – today
- 2022
[j174]Pengmiao Zhang
, Ajitesh Srivastava, Ta-Yang Wang, César A. F. De Rose, Rajgopal Kannan, Viktor K. Prasanna:
C-MemMAP: clustering-driven compact, adaptable, and generalizable meta-LSTM models for memory access prediction. Int. J. Data Sci. Anal. 13(1): 3-16 (2022)- [j173]Kartik Lakhotia, Fabrizio Petrini, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Allreduce With In-Network Reduction on Intel PIUMA. IEEE Micro 42(2): 44-52 (2022) - [j172]Yuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
PPOAccel: A High-Throughput Acceleration Framework for Proximal Policy Optimization. IEEE Trans. Parallel Distributed Syst. 33(9): 2066-2078 (2022) - [j171]Ken Eguro, Stephen Neuendorffer, Viktor K. Prasanna, Hongbo Rong:
Introduction to Special Issue on FPGAs in Data Centers. ACM Trans. Reconfigurable Technol. Syst. 15(2): 11:1-11:2 (2022) - [c530]Diyi Hu, Chi Zhang, Viktor K. Prasanna, Bhaskar Krishnamachari:
Intelligent Communication over Realistic Wireless Networks in Multi-Agent Cooperative Games. AAMAS 2022: 1627-1629 - [c529]Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
NTTGen: a framework for generating low latency NTT implementations on FPGA. CF 2022: 30-39 - [c528]Yuan Meng, Chi Zhang, Viktor K. Prasanna:
FPGA acceleration of deep reinforcement learning using on-chip replay management. CF 2022: 40-48 - [c527]Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna:
Fine-grained address segmentation for attention-based variable-degree prefetching. CF 2022: 103-112 - [c526]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
End-to-End Acceleration of Homomorphic Encrypted CNN Inference on FPGAs. FPGA 2022: 51 - [c525]Yi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna:
HP-GNN: Generating High Throughput GNN Training Implementation on CPU-FPGA Heterogeneous Platform. FPGA 2022: 123-133 - [c524]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
DecGNN: A Framework for Mapping Decoupled GNN Models onto CPU-FPGA Heterogeneous Platform. FPGA 2022: 154 - [i40]Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen:
Decoupling the Depth and Scope of Graph Neural Networks. CoRR abs/2201.07858 (2022) - [i39]Hongkuan Zhou, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl Busart:
Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA. CoRR abs/2203.05095 (2022) - [i38]Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware. CoRR abs/2203.15534 (2022) - [i37]Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna:
Fine-Grained Address Segmentation for Attention-Based Variable-Degree Prefetching. CoRR abs/2205.02269 (2022) - 2021
- [j170]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, efficient and scalable training of Graph Neural Networks. J. Parallel Distributed Comput. 147: 166-183 (2021) - [j169]Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning. Proc. VLDB Endow. 14(9): 1597-1605 (2021) - [j168]Aggelos Lazaris, Viktor K. Prasanna:
An LSTM Framework for Software-Defined Measurement. IEEE Trans. Netw. Serv. Manag. 18(1): 855-869 (2021) - [c523]Chi Zhang, Sanmukh R. Kuppannagari, Viktor K. Prasanna:
BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement Learning. ACML 2021: 204-219 - [c522]Hongkuan Zhou, James Orme-Rogers, Rajgopal Kannan, Viktor K. Prasanna:
SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings. CIKM 2021: 3667-3671 - [c521]Sanmukh R. Kuppannagari, Yao Fu, Chung Ming Cheung, Viktor K. Prasanna:
Spatio-Temporal Missing Data Imputation for Smart Power Grids. e-Energy 2021: 458-465 - [c520]Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna:
BoostGCN: A Framework for Optimizing GCN Inference on FPGA. FCCM 2021: 29-39 - [c519]Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna:
A Framework for Optimizing GCN Inference on FPGA. FPGA 2021: 145 - [c518]Yuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference. FPGA 2021: 183-193 - [c517]Tian Ye, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Performance Modeling and FPGA Acceleration of Homomorphic Encrypted Convolution. FPL 2021: 115-121 - [c516]Nathaniel Peura, Yuan Meng, Sanmukh R. Kuppannagari, Viktor K. Prasanna:
FGYM: Toolkit for Benchmarking FPGA based Reinforcement Learning Algorithms. FPL 2021: 404 - [c515]Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K. Prasanna:
Parallel Actors and Learners: A Framework for Generating Scalable RL Implementations. HiPC 2021: 1-10 - [c514]Ta-Yang Wang, William Chang, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Monte Carlo Tree Search for Task Mapping onto Heterogeneous Platforms. HiPC 2021: 63-70 - [c513]Yuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
How to Avoid Zero-Spacing in Fractionally-Strided Convolution? A Hardware-Algorithm Co-Design Methodology. HiPC 2021: 81-90 - [c512]Madhav Aggarwal, Bingyi Zhang, Viktor K. Prasanna:
Performance of Local Push Algorithms for Personalized PageRank on Multi-core Platforms. HiPC 2021: 370-375 - [c511]Kartik Lakhotia, Fabrizio Petrini, Rajgopal Kannan, Viktor K. Prasanna:
In-network reductions on multi-dimensional HyperX. HOTI 2021: 1-8 - [c510]Sasindu Wijeratne, Sanket Pattnaik, Zhiyu Chen, Rajgopal Kannan, Viktor K. Prasanna:
Programmable FPGA-based Memory Controller. HOTI 2021: 43-51 - [c509]Yi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna:
GCN Inference Acceleration using High-Level Synthesis. HPEC 2021: 1-6 - [c508]Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna:
Reconfigurable Low-latency Memory System for Sparse Matricized Tensor Times Khatri-Rao Product on FPGA. HPEC 2021: 1-7 - [c507]Bingyi Zhang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Efficient Neighbor-Sampling-based GNN Training on CPU-FPGA Heterogeneous Platform. HPEC 2021: 1-7 - [c506]Chung Ming Cheung, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Leveraging Spatial Information in Smart Grids using STGCN for Short-Term Load Forecasting. IC3 2021: 159-167 - [c505]Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen:
Decoupling the Depth and Scope of Graph Neural Networks. NeurIPS 2021: 19665-19679 - [c504]Naifeng Zhang, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
GenMAT: A General-Purpose Machine Learning-Driven Auto-Tuner for Heterogeneous Platforms. PEHC@SC 2021: 1-9 - [c503]Tian Ye, Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
FPGA Acceleration of Number Theoretic Transform. ISC 2021: 98-117 - [i36]Ajitesh Srivastava, Tianjian Xu, Viktor K. Prasanna:
The EpiBench Platform to Propel AI/ML-based Epidemic Forecasting: A Prototype Demonstration Reaching Human Expert-level Performance. CoRR abs/2102.02842 (2021) - [i35]Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning. CoRR abs/2105.04528 (2021) - [i34]Ruizhi Zhang, Sasindu Wijeratne, Yang Yang, Sanmukh R. Kuppannagari, Viktor K. Prasanna:
A High Throughput Parallel Hash Table on FPGA using XOR-based Memory. CoRR abs/2108.03390 (2021) - [i33]Sasindu Wijeratne, Sanket Pattnaik, Zhiyu Chen, Rajgopal Kannan, Viktor K. Prasanna:
Programmable FPGA-based Memory Controller. CoRR abs/2108.09601 (2021) - [i32]Hongkuan Zhou, James Orme-Rogers, Rajgopal Kannan, Viktor K. Prasanna:
SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings. CoRR abs/2109.04550 (2021) - [i31]Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna:
Reconfigurable Low-latency Memory System for Sparse Matricized Tensor Times Khatri-Rao Product on FPGA. CoRR abs/2109.08874 (2021) - [i30]Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K. Prasanna:
BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement Learning. CoRR abs/2110.00894 (2021) - [i29]Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K. Prasanna:
Parallel Actors and Learners: A Framework for Generating Scalable RL Implementations. CoRR abs/2110.01101 (2021) - [i28]Kartik Lakhotia, Rajgopal Kannan, Viktor K. Prasanna:
Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery. CoRR abs/2110.12511 (2021) - [i27]Yi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna:
HP-GNN: Generating High Throughput GNN Training Implementation on CPU-FPGA Heterogeneous Platform. CoRR abs/2112.11684 (2021) - 2020
- [j167]Kartik Lakhotia, Rajgopal Kannan, Viktor K. Prasanna, César A. F. De Rose:
RECEIPT: REfine CoarsE-grained IndePendent Tasks for Parallel Tip decomposition of Bipartite Graphs. Proc. VLDB Endow. 14(3): 404-417 (2020) - [j166]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) - [j165]Shijie Zhou, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Stochastic Gradient Descent Based Matrix Factorization on FPGA. IEEE Trans. Parallel Distributed Syst. 31(8): 1897-1911 (2020) - [c502]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
Hardware Acceleration of Large Scale GCN Inference. ASAP 2020: 61-68 - [c501]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 - [c500]Yuan Meng, Sanmukh R. Kuppannagari, Viktor K. Prasanna:
Accelerating Proximal Policy Optimization on CPU-FPGA Heterogeneous Platforms. FCCM 2020: 19-27 - [c499]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
Accelerating Large Scale GCN Inference on FPGA. FCCM 2020: 241 - [c498]Hanqing Zeng, Viktor K. Prasanna:
GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms. FPGA 2020: 255-265 - [c497]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 - [c496]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 - [c495]Ajitesh Srivastava, Naifeng Zhang, Rajgopal Kannan, Viktor K. Prasanna:
Towards High Performance, Portability, and Productivity: Lightweight Augmented Neural Networks for Performance Prediction. HiPC 2020: 21-30 - [c494]Yuan Meng, Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
How to Efficiently Train Your AI Agent? Characterizing and Evaluating Deep Reinforcement Learning on Heterogeneous Platforms. HPEC 2020: 1-7 - [c493]Ta-Yang Wang, Ajitesh Srivastava, Viktor K. Prasanna:
A Framework for Task Mapping onto Heterogeneous Platforms. HPEC 2020: 1-6 - [c492]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
Accelerator Design and Performance Modeling for Homomorphic Encrypted CNN Inference. HPEC 2020: 1-7 - [c491]Ruizhi Zhang, Sasindu Wijeratne, Yang Yang, Sanmukh R. Kuppannagari, Viktor K. Prasanna:
A High Throughput Parallel Hash Table on FPGA using XOR-based Memory. HPEC 2020: 1-7 - [c490]Yang Yang, Sanmukh R. Kuppannagari, Viktor K. Prasanna:
A High Throughput Parallel Hash Table Accelerator on HBM-enabled FPGAs. FPT 2020: 148-153 - [c489]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
GraphSAINT: Graph Sampling Based Inductive Learning Method. ICLR 2020 - [c488]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 - [c487]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 - [c486]Pengmiao Zhang, Ajitesh Srivastava, Benjamin Brooks, Rajgopal Kannan, Viktor K. Prasanna:
RAOP: Recurrent Neural Network Augmented Offset Prefetcher. MEMSYS 2020: 352-362 - [c485]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 - [c484]Connor Imes, Alexei Colin, Naifeng Zhang, Ajitesh Srivastava, Viktor K. Prasanna, John Paul Walters:
Compiler Abstractions and Runtime for Extreme-scale SAR and CFD Workloads. ESPM2@SC 2020: 1-7 - [c483]Yang Yang, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
FASTHash: FPGA-Based High Throughput Parallel Hash Table. ISC 2020: 3-22 - [i26]Hanqing Zeng, Viktor K. Prasanna:
GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms. CoRR abs/2001.02498 (2020) - [i25]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) - [i24]Ajitesh Srivastava, Viktor K. Prasanna:
Learning to Forecast and Forecasting to Learn from the COVID-19 Pandemic. CoRR abs/2004.11372 (2020) - [i23]Ajitesh Srivastava, Viktor K. Prasanna:
Data-driven Identification of Number of Unreported Cases for COVID-19: Bounds and Limitations. CoRR abs/2006.02127 (2020) - [i22]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) - [i21]Ajitesh Srivastava, Tianjian Xu, Viktor K. Prasanna:
Fast and Accurate Forecasting of COVID-19 Deaths Using the SIkJα Model. CoRR abs/2007.05180 (2020) - [i20]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, Efficient and Scalable Training of Graph Neural Networks. CoRR abs/2010.03166 (2020) - [i19]Kartik Lakhotia, Rajgopal Kannan, Viktor K. Prasanna, César A. F. De Rose:
RECEIPT: REfine CoarsE-grained IndePendent Tasks for Parallel Tip decomposition of Bipartite Graphs. CoRR abs/2010.08695 (2020) - [i18]Yuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference. CoRR abs/2012.00912 (2020) - [i17]Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Andrey Malevich, Ren Chen:
Deep Graph Neural Networks with Shallow Subgraph Samplers. CoRR abs/2012.01380 (2020)
2010 – 2019
- 2019
- [j164]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) - [j163]Muhammad Rizwan Saeed, Charalampos Chelmis, Viktor K. Prasanna:
Extracting entity-specific substructures for RDF graph embeddings. Semantic Web 10(6): 1087-1108 (2019) - [j162]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) - [j161]Ranjan Pal, Pan Hui, Viktor K. Prasanna:
Privacy Engineering for the Smart Micro-Grid. IEEE Trans. Knowl. Data Eng. 31(5): 965-980 (2019) - [j160]Shijie Zhou, Rajgopal Kannan, Viktor K. Prasanna, Guna Seetharaman, Qing Wu:
HitGraph: High-throughput Graph Processing Framework on FPGA. IEEE Trans. Parallel Distributed Syst. 30(10): 2249-2264 (2019) - [c482]Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
RecANt: Network-based Recruitment for Active Fake News Correction. IEEE BigData 2019: 940-949 - [c481]Kartik Lakhotia, Rajgopal Kannan, Aditya Gaur, Ajitesh Srivastava, Viktor K. Prasanna:
Parallel edge-based sampling for static and dynamic graphs. CF 2019: 125-134 - [c480]Aggelos Lazaris, Viktor K. Prasanna:
Deep Learning Models For Aggregated Network Traffic Prediction. CNSM 2019: 1-5 - [c479]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Approximate Scheduling of DERs with Discrete Complex Injections. e-Energy 2019: 204-214 - [c478]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 - [c477]Rachit Rajat, Hanqing Zeng, Viktor K. Prasanna:
A Flexible Design Automation Tool for Accelerating Quantized Spectral CNNs. FPL 2019: 144-150 - [c476]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 - [c475]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 - [c474]Sanmukh R. Kuppannagari, Rachit Rajat, Rajgopal Kannan, Aravind Dasu, Viktor K. Prasanna:
IP Cores for Graph Kernels on FPGAs. HPEC 2019: 1-7 - [c473]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 - [c472]Aggelos Lazaris, Viktor K. Prasanna:
An LSTM Framework For Modeling Network Traffic. IM 2019: 19-24 - [c471]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 - [c470]Viktor K. Prasanna:
HCW 2019 Keynote Address. IPDPS Workshops 2019: 5 - [c469]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, Efficient and Scalable Graph Embedding. IPDPS 2019: 462-471 - [c468]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 - [c467]Akshit Goel, Sanmukh R. Kuppannagari, Yang Yang, Ajitesh Srivastava, Viktor K. Prasanna:
Parallel Totally Induced Edge Sampling on FPGAs. PARCO 2019: 671-680 - [c466]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 - [c465]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
- [j159]Muhammad Rizwan Saeed, Charalampos Chelmis, Viktor K. Prasanna:
ASQFor: Automatic SPARQL query formulation for the non-expert. AI Commun. 31(1): 19-32 (2018) - [j158]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) - [j157]Da Tong, Viktor K. Prasanna:
Sketch Acceleration on FPGA and its Applications in Network Anomaly Detection. IEEE Trans. Parallel Distributed Syst. 29(4): 929-942 (2018) - [c464]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 - [c463]Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
FActCheck: Keeping Activation of Fake News at Check. AAMAS 2018: 2079-2081 - [c462]Shijie Zhou, Rajgopal Kannan, Hanqing Zeng, Viktor K. Prasanna:
An FPGA framework for edge-centric graph processing. CF 2018: 69-77 - [c461]Hanqing Zeng, Ren Chen, Chi Zhang, Viktor K. Prasanna:
A Framework for Generating High Throughput CNN Implementations on FPGAs. FPGA 2018: 117-126 - [c460]Shijie Zhou, Rajgopal Kannan, Yu Min, Viktor K. Prasanna:
FASTCF: FPGA-based Accelerator for STochastic-Gradient-Descent-based Collaborative Filtering. FPGA 2018: 259-268 - [c459]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 - [c458]