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2020 – today
- 2023
[j44]Chung Ming Cheung
, Sanmukh Rao Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Behind-the-Meter Solar Generation Disaggregation at Varying Aggregation Levels Using Consumer Mixture Models. IEEE Trans. Sustain. Comput. 8(1): 43-55 (2023)- [c117]Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
A Framework for Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform via on-chip Dynamic Tree Management. FPGA 2023: 235-245 - [c116]Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Sparse MTTKRP for Tensor Decomposition on FPGA. FPGA 2023: 259-269 - [i40]Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Accurate, Low-latency, Efficient SAR Automatic Target Recognition on FPGA. CoRR abs/2301.01454 (2023) - [i39]Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna:
HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN. CoRR abs/2304.10013 (2023) - [i38]Bingyi Zhang, Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Graph Neural Network for Accurate and Low-complexity SAR ATR. CoRR abs/2305.07119 (2023) - 2022
- [j43]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) - [j42]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) - [j41]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) - [c115]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 - [c114]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 - [c113]Ta-Yang Wang, Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna:
Throughput optimization in heterogeneous MIMO networks: a GNN-based approach. GNNet@CoNEXT 2022: 42-47 - [c112]Pengmiao Zhang, Rajgopal Kannan, Anant V. Nori, Viktor K. Prasanna:
A2P: Attention-based Memory Access Prediction for Graph Analytics. DATA 2022: 135-145 - [c111]Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Towards Programmable Memory Controller for Tensor Decomposition. DATA 2022: 468-475 - [c110]Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
FPGA Accelerator for Homomorphic Encrypted Sparse Convolutional Neural Network Inference. FCCM 2022: 1-9 - [c109]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
End-to-End Acceleration of Homomorphic Encrypted CNN Inference on FPGAs. FPGA 2022: 51 - [c108]Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Accurate, Low-latency, Efficient SAR Automatic Target Recognition on FPGA. FPL 2022: 1-8 - [c107]Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform. FPL 2022: 176-182 - [c106]Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Bandwidth Efficient Homomorphic Encrypted Matrix Vector Multiplication Accelerator on FPGA. FPT 2022: 1-9 - [c105]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
FPGA Acceleration of Fully Homomorphic Encryption over the Torus. HPEC 2022: 1-7 - [c104]Pengmiao Zhang, Rajgopal Kannan, Xiangzhi Tong, Anant V. Nori, Viktor K. Prasanna:
SHARP: Software Hint-Assisted Memory Access Prediction for Graph Analytics. HPEC 2022: 1-8 - [c103]Hongkuan Zhou, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA. IPDPS 2022: 1108-1117 - [c102]Tian Ye, Sanmukh R. Kuppannagari, César A. F. De Rose, Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna:
Estimating the Impact of Communication Schemes for Distributed Graph Processing. ISPDC 2022: 49-56 - [c101]Pengmiao Zhang, Rajgopal Kannan, Ajitesh Srivastava, Anant V. Nori, Viktor K. Prasanna:
ReSemble: Reinforced Ensemble Framework for Data Prefetching. SC 2022: 81:1-81:14 - [i37]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) - [i36]Hongkuan Zhou, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA. CoRR abs/2203.05095 (2022) - [i35]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) - [i34]Tian Xie, Rajgopal Kannan, C.-C. Jay Kuo:
GraphHop++: New Insights into GraphHop and Its Enhancement. CoRR abs/2204.08646 (2022) - [i33]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) - [i32]Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna:
TransforMAP: Transformer for Memory Access Prediction. CoRR abs/2205.14778 (2022) - [i31]Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Towards Programmable Memory Controller for Tensor Decomposition. CoRR abs/2207.08298 (2022) - [i30]Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform. CoRR abs/2208.11208 (2022) - [i29]Pengmiao Zhang, Rajgopal Kannan, Viktor K. Prasanna:
Phases, Modalities, Temporal and Spatial Locality: Domain Specific ML Prefetcher for Accelerating Graph Analytics. CoRR abs/2212.05250 (2022) - 2021
- [j40]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) - [j39]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) - [c100]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 - [c99]Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna:
BoostGCN: A Framework for Optimizing GCN Inference on FPGA. FCCM 2021: 29-39 - [c98]Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna:
A Framework for Optimizing GCN Inference on FPGA. FPGA 2021: 145 - [c97]Yuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference. FPGA 2021: 183-193 - [c96]Tian Ye, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Performance Modeling and FPGA Acceleration of Homomorphic Encrypted Convolution. FPL 2021: 115-121 - [c95]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 - [c94]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 - [c93]Kartik Lakhotia, Fabrizio Petrini, Rajgopal Kannan, Viktor K. Prasanna:
In-network reductions on multi-dimensional HyperX. HOTI 2021: 1-8 - [c92]Sasindu Wijeratne, Sanket Pattnaik, Zhiyu Chen, Rajgopal Kannan, Viktor K. Prasanna:
Programmable FPGA-based Memory Controller. HOTI 2021: 43-51 - [c91]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 - [c90]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 - [c89]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 - [c88]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 - [c87]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 - [c86]Tian Ye, Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
FPGA Acceleration of Number Theoretic Transform. ISC 2021: 98-117 - [i28]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) - [i27]Sasindu Wijeratne, Sanket Pattnaik, Zhiyu Chen, Rajgopal Kannan, Viktor K. Prasanna:
Programmable FPGA-based Memory Controller. CoRR abs/2108.09601 (2021) - [i26]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) - [i25]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) - [i24]Kartik Lakhotia, Rajgopal Kannan, Viktor K. Prasanna:
Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery. CoRR abs/2110.12511 (2021) - 2020
- [j38]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) - [j37]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) - [j36]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) - [c85]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 - [c84]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 - [c83]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 - [c82]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 - [c81]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
Accelerator Design and Performance Modeling for Homomorphic Encrypted CNN Inference. HPEC 2020: 1-7 - [c80]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
GraphSAINT: Graph Sampling Based Inductive Learning Method. ICLR 2020 - [c79]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 - [c78]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 - [c77]Pengmiao Zhang, Ajitesh Srivastava, Benjamin Brooks, Rajgopal Kannan, Viktor K. Prasanna:
RAOP: Recurrent Neural Network Augmented Offset Prefetcher. MEMSYS 2020: 352-362 - [c76]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 - [c75]Yang Yang, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
FASTHash: FPGA-Based High Throughput Parallel Hash Table. ISC 2020: 3-22 - [i23]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) - [i22]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) - [i21]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) - [i20]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) - [i19]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
- [j35]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) - [j34]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) - [j33]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) - [c74]Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
RecANt: Network-based Recruitment for Active Fake News Correction. IEEE BigData 2019: 940-949 - [c73]Kartik Lakhotia, Rajgopal Kannan, Aditya Gaur, Ajitesh Srivastava, Viktor K. Prasanna:
Parallel edge-based sampling for static and dynamic graphs. CF 2019: 125-134 - [c72]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Approximate Scheduling of DERs with Discrete Complex Injections. e-Energy 2019: 204-214 - [c71]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 - [c70]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 - [c69]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 - [c68]Sanmukh R. Kuppannagari, Rachit Rajat, Rajgopal Kannan, Aravind Dasu, Viktor K. Prasanna:
IP Cores for Graph Kernels on FPGAs. HPEC 2019: 1-7 - [c67]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 - [c66]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 - [c65]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, Efficient and Scalable Graph Embedding. IPDPS 2019: 462-471 - [c64]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 - [c63]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 - [c62]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 - [i18]Kartik Lakhotia, Qing Dong, Rajgopal Kannan, Viktor K. Prasanna:
Planting Trees for scalable and efficient Canonical Hub Labeling. CoRR abs/1907.00140 (2019) - [i17]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
GraphSAINT: Graph Sampling Based Inductive Learning Method. CoRR abs/1907.04931 (2019) - [i16]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) - [i15]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
- [j32]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) - [c61]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 - [c60]Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
FActCheck: Keeping Activation of Fake News at Check. AAMAS 2018: 2079-2081 - [c59]Shijie Zhou, Rajgopal Kannan, Hanqing Zeng, Viktor K. Prasanna:
An FPGA framework for edge-centric graph processing. CF 2018: 69-77 - [c58]Shijie Zhou, Rajgopal Kannan, Yu Min, Viktor K. Prasanna:
FASTCF: FPGA-based Accelerator for STochastic-Gradient-Descent-based Collaborative Filtering. FPGA 2018: 259-268 - [c57]Chung Ming Cheung, Rajgopal Kannan, Viktor K. Prasanna:
Temporal ensemble learning of univariate methods for short term load forecasting. ISGT 2018: 1-5 - [c56]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Risk aware net load balancing in micro grids with high DER penetration. ISGT 2018: 1-5 - [c55]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 - [c54]Costas Busch, Rajgopal Kannan:
Polynomial Time Equilibria in Bottleneck Congestion Games. EC 2018: 393-409 - [c53]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 - [c52]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 - [c51]Kartik Lakhotia, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating PageRank using Partition-Centric Processing. USENIX Annual Technical Conference 2018: 427-440 - [i14]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) - [i13]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, Efficient and Scalable Graph Embedding. CoRR abs/1810.11899 (2018) - 2017
- [j31]Michael F. Stewart, Rajgopal Kannan, Amit Dvir, Bhaskar Krishnamachari:
CASPaR: Congestion avoidance shortest path routing for delay tolerant networks. Int. J. Distributed Sens. Networks 13(11) (2017) - [j30]Saikat Basu, Manohar Karki, Sangram Ganguly, Robert DiBiano, Supratik Mukhopadhyay, Shreekant Gayaka, Rajgopal Kannan, Ramakrishna R. Nemani:
Learning Sparse Feature Representations Using Probabilistic Quadtrees and Deep Belief Nets. Neural Process. Lett. 45(3): 855-867 (2017) - [c50]Michail Misyrlis, Chung Ming Cheung, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Spatio-Temporal Modeling of Criminal Activity. SocialSens@CPSWeek 2017: 3-8 - [c49]Kartik Lakhotia, Shreyas G. Singapura, Rajgopal Kannan, Viktor K. Prasanna:
ReCALL: Reordered Cache Aware Locality Based Graph Processing. HiPC 2017: 273-282 - [c48]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 - [c47]Shreyas G. Singapura, Rajgopal Kannan, Viktor K. Prasanna:
Optimal data layout for block-level random accesses to scratchpad. HPEC 2017: 1-7 - [c46]Shreyas G. Singapura, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
OSCAR: Optimizing SCrAtchpad reuse for graph processing. HPEC 2017: 1-7 - [c45]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 - [c44]Charith Wickramaarachchi, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
PReSS towards a secure smart grid: Protection recommendations against smart spoofing. ISGT 2017: 1-5 - [c43]Shijie Zhou, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating low rank matrix completion on FPGA. ReConFig 2017: 1-7 - [c42]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 - [i12]Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Optimal Net-Load Balancing in Smart Grids with High PV Penetration. CoRR abs/1709.00644 (2017) - [i11]