Viktor K. Prasanna - researchr alias

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Viewing Publication 1 - 100 from 741

2024

HitGNN: High-Throughput GNN Training Framework on CPU+Multi-FPGA Heterogeneous PlatformYi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna. tpds, 35(5):707-719, May 2024. [doi]

2023

A Framework for Mapping DRL Algorithms With Prioritized Replay Buffer Onto Heterogeneous PlatformsChi Zhang 0022, Yuan Meng, Viktor K. Prasanna. tpds, 34(6):1816-1829, June 2023. [doi]

FPGA Acceleration of Rotation in Homomorphic Encryption Using Dynamic Data LayoutYang Yang 0111, Weihang Long, Rajgopal Kannan, Viktor K. Prasanna. fpl 2023: 174-181 [doi]

Exploiting On-Chip Heterogeneity of Versal Architecture for GNN Inference AccelerationPaul Chen, Pavan Manjunath, Sasindu Wijeratne, Bingyi Zhang, Viktor K. Prasanna. fpl 2023: 219-227 [doi]

Behind-the-Meter Solar Generation Disaggregation at Varying Aggregation Levels Using Consumer Mixture ModelsChung-Ming Cheung, Sanmukh Rao Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna. tsusc, 8(1):43-55, January - March 2023. [doi]

Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph DiscoveryKartik Lakhotia, Rajgopal Kannan, Viktor K. Prasanna. topc, 10(2), June 2023. [doi]

HyScale-GNN: A Scalable Hybrid GNN Training System on Single-Node Heterogeneous ArchitectureYi-Chien Lin, Viktor K. Prasanna. ipps 2023: 557-567 [doi]

A Framework for Graph Machine Learning on Heterogeneous ArchitectureYi-Chien Lin, Viktor K. Prasanna. fccm 2023: 245-246 [doi]

ME- ViT: A Single-Load Memory-Efficient FPGA Accelerator for Vision TransformersKyle Marino, Pengmiao Zhang, Viktor K. Prasanna. hipc 2023: 213-223 [doi]

A Framework for Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform via on-chip Dynamic Tree ManagementYuan Meng, Rajgopal Kannan, Viktor K. Prasanna. fpga 2023: 235-245 [doi]

Accelerating Deep Neural Network guided MCTS using Adaptive ParallelismYuan Meng, Qian Wang, Tianxin Zu, Viktor K. Prasanna. sc 2023: 766-769 [doi]

Training Heterogeneous Graph Neural Networks using Bandit SamplingTa-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna. CIKM 2023: 4345-4349 [doi]

Characterizing Speed Performance of Multi-Agent Reinforcement LearningSamuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna. data 2023: 327-334 [doi]

Dynasor: A Dynamic Memory Layout for Accelerating Sparse MTTKRP for Tensor Decomposition on Multi-core CPUSasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna. sbac-pad 2023: 23-33 [doi]

Accelerating Sparse MTTKRP for Tensor Decomposition on FPGASasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna. fpga 2023: 259-269 [doi]

Dynasparse: Accelerating GNN Inference through Dynamic Sparsity ExploitationBingyi Zhang, Viktor K. Prasanna. ipps 2023: 233-244 [doi]

Phases, Modalities, Spatial and Temporal Locality: Domain Specific ML Prefetcher for Accelerating Graph AnalyticsPengmiao Zhang, Rajgopal Kannan, Viktor K. Prasanna. sc 2023: [doi]

GraphAGILE: An FPGA-Based Overlay Accelerator for Low-Latency GNN InferenceBingyi Zhang, Hanqing Zeng, Viktor K. Prasanna. tpds, 34(9):2580-2597, September 2023. [doi]

HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNNHongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna. infocom 2023: 1-10 [doi]

DistTGL: Distributed Memory-Based Temporal Graph Neural Network TrainingHongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna. sc 2023: [doi]

2022

29th Reconfigurable Architectures Workshop (RAW 2022)Jürgen Becker 0001, Lana Josipovic, Viktor K. Prasanna, Marco D. Santambrogio, Ramachandran Vaidyanathan. ipps 2022: 65-66 [doi]

Safe Building HVAC Control via Batch Reinforcement LearningChi Zhang 0022, Sanmukh Rao Kuppannagari, Viktor K. Prasanna. tsusc, 7(4):923-934, 2022. [doi]

Bandwidth Efficient Homomorphic Encrypted Matrix Vector Multiplication Accelerator on FPGAYang Yang 0111, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. fpt 2022: 1-9 [doi]

NTTGen: a framework for generating low latency NTT implementations on FPGAYang Yang 0111, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. cf 2022: 30-39 [doi]

FPGA Accelerator for Homomorphic Encrypted Sparse Convolutional Neural Network InferenceYang Yang 0111, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. fccm 2022: 1-9 [doi]

Introduction to Special Issue on FPGAs in Data Centers, Part IIKen Eguro, Stephen Neuendorffer, Viktor K. Prasanna, Hongbo Rong. trets, 15(3), 2022. [doi]

Introduction to Special Issue on FPGAs in Data CentersKen Eguro, Stephen Neuendorffer, Viktor K. Prasanna, Hongbo Rong. trets, 15(2), 2022. [doi]

Intelligent Communication over Realistic Wireless Networks in Multi-Agent Cooperative GamesDiyi Hu, Chi Zhang 0022, Viktor K. Prasanna, Bhaskar Krishnamachari. atal 2022: 1627-1629 [doi]

Learning Practical Communication Strategies in Cooperative Multi-Agent Reinforcement LearningDiyi Hu, Chi Zhang, Viktor K. Prasanna, Bhaskar Krishnamachari. acml 2022: 467-482 [doi]

Hypersort: High-performance Parallel Sorting on HBM-enabled FPGASoundarya Jayaraman, Bingyi Zhang, Viktor K. Prasanna. fpt 2022: 1-11 [doi]

Accelerating Prefix Scan with in-network computing on Intel PIUMAKartik Lakhotia, Fabrizio Petrini, Rajopgal Kannan, Viktor K. Prasanna. hipc 2022: 59-68 [doi]

Accelerating Allreduce With In-Network Reduction on Intel PIUMAKartik Lakhotia, Fabrizio Petrini, Rajgopal Kannan, Viktor K. Prasanna. micro, 42(2):44-52, 2022. [doi]

Accelerating GNN Training on CPU+Multi-FPGA Heterogeneous PlatformYi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna. carla 2022: 16-30 [doi]

HP-GNN: Generating High Throughput GNN Training Implementation on CPU-FPGA Heterogeneous PlatformYi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna. fpga 2022: 123-133 [doi]

End to End Framework for CNN Acceleration on FPGAs with Dynamic Algorithm MappingHaomei Liu, Yuan Meng, Sanmukh Rao Kuppannagari, Viktor K. Prasanna. ic3 2022: 696-700 [doi]

Accelerator Design and Exploration for Deformable Convolution NetworksYuan Meng, Hongjiang Men, Viktor K. Prasanna. sips 2022: 1-6 [doi]

Accelerating Deformable Convolution NetworksYuan Meng, Hongjiang Men, Viktor K. Prasanna. fccm 2022: 1 [doi]

FPGA acceleration of deep reinforcement learning using on-chip replay managementYuan Meng, Chi Zhang 0022, Viktor K. Prasanna. cf 2022: 40-48 [doi]

Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous PlatformYuan Meng, Rajgopal Kannan, Viktor K. Prasanna. fpl 2022: 176-182 [doi]

PPOAccel: A High-Throughput Acceleration Framework for Proximal Policy OptimizationYuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. tpds, 33(9):2066-2078, 2022. [doi]

Computational Models for Cascades in Massive GraphsAjitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna. In David A. Bader, editor, Massive Graph Analytics. pages 377-395, Chapman and Hall/CRC, 2022. [doi]

Throughput optimization in heterogeneous MIMO networks: a GNN-based approachTa-Yang Wang, Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna. conext 2022: 42-47 [doi]

Performance Modeling Sparse MTTKRP Using Optical Static Random Access Memory on FPGASasindu Wijeratne, Akhilesh R. Jaiswal, Ajey P. Jacob, Bingyi Zhang, Viktor K. Prasanna. hpec 2022: 1-7 [doi]

Towards Programmable Memory Controller for Tensor DecompositionSasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna. data 2022: 468-475 [doi]

FPGA Acceleration of Fully Homomorphic Encryption over the TorusTian Ye, Rajgopal Kannan, Viktor K. Prasanna. hpec 2022: 1-7 [doi]

Estimating the Impact of Communication Schemes for Distributed Graph ProcessingTian Ye, Sanmukh R. Kuppannagari, César A. F. De Rose, Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna. ispdc 2022: 49-56 [doi]

End-to-End Acceleration of Homomorphic Encrypted CNN Inference on FPGAsTian Ye, Rajgopal Kannan, Viktor K. Prasanna. fpga 2022: 51 [doi]

Input Feature Pruning for Accelerating GNN Inference on Heterogeneous PlatformsJason Yik, Sanmukh R. Kuppannagari, Hanqing Zeng, Viktor K. Prasanna. hipc 2022: 282-291 [doi]

Low-latency Mini-batch GNN Inference on CPU-FPGA Heterogeneous PlatformBingyi Zhang, Hanqing Zeng, Viktor K. Prasanna. hipc 2022: 11-21 [doi]

Fine-grained address segmentation for attention-based variable-degree prefetchingPengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna. cf 2022: 103-112 [doi]

Accurate, Low-latency, Efficient SAR Automatic Target Recognition on FPGABingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart. fpl 2022: 1-8 [doi]

ReSemble: Reinforced Ensemble Framework for Data PrefetchingPengmiao Zhang, Rajgopal Kannan, Ajitesh Srivastava, Anant V. Nori, Viktor K. Prasanna. sc 2022: 1-14 [doi]

DecGNN: A Framework for Mapping Decoupled GNN Models onto CPU-FPGA Heterogeneous PlatformBingyi Zhang, Hanqing Zeng, Viktor K. Prasanna. fpga 2022: 154 [doi]

Modeling the Energy Efficiency of GEMM using Optical Random Access MemoryBingyi Zhang, Akhilesh R. Jaiswal, Clynn Mathew, Ravi Teja Lakkireddy, Ajey P. Jacob, Sasindu Wijeratne, Viktor K. Prasanna. hpec 2022: 1-7 [doi]

SHARP: Software Hint-Assisted Memory Access Prediction for Graph AnalyticsPengmiao Zhang, Rajgopal Kannan, Xiangzhi Tong, Anant V. Nori, Viktor K. Prasanna. hpec 2022: 1-8 [doi]

A2P: Attention-based Memory Access Prediction for Graph AnalyticsPengmiao Zhang, Rajgopal Kannan, Anant V. Nori, Viktor K. Prasanna. data 2022: 135-145 [doi]

C-MemMAP: clustering-driven compact, adaptable, and generalizable meta-LSTM models for memory access predictionPengmiao Zhang, Ajitesh Srivastava, Ta-Yang Wang, César A. F. De Rose, Rajgopal Kannan, Viktor K. Prasanna. ijdsa, 13(1):3-16, 2022. [doi]

Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGAHongkuan Zhou, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl Busart. ipps 2022: 1108-1117 [doi]

2021

Parallel Actors and Learners: A Framework for Generating Scalable RL ImplementationsChi Zhang 0022, Sanmukh Rao Kuppannagari, Viktor K. Prasanna. hipc 2021: 1-10 [doi]

Performance of Local Push Algorithms for Personalized PageRank on Multi-core PlatformsMadhav Aggarwal, Bingyi Zhang, Viktor K. Prasanna. hipc 2021: 370-375 [doi]

Leveraging Spatial Information in Smart Grids using STGCN for Short-Term Load ForecastingChung-Ming Cheung, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. ic3 2021: 159-167 [doi]

Spatio-Temporal Missing Data Imputation for Smart Power GridsSanmukh R. Kuppannagari, Yao Fu, Chung-Ming Cheung, Viktor K. Prasanna. eenergy 2021: 458-465 [doi]

In-network reductions on multi-dimensional HyperXKartik Lakhotia, Fabrizio Petrini, Rajgopal Kannan, Viktor K. Prasanna. hoti 2021: 1-8 [doi]

An LSTM Framework for Software-Defined MeasurementAggelos Lazaris, Viktor K. Prasanna. tnsm, 18(1):855-869, 2021. [doi]

GCN Inference Acceleration using High-Level SynthesisYi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna. hpec 2021: 1-6 [doi]

DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN InferenceYuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. fpga 2021: 183-193 [doi]

How to Avoid Zero-Spacing in Fractionally-Strided Convolution? A Hardware-Algorithm Co-Design MethodologyYuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. hipc 2021: 81-90 [doi]

FGYM: Toolkit for Benchmarking FPGA based Reinforcement Learning AlgorithmsNathaniel Peura, Yuan Meng, Sanmukh R. Kuppannagari, Viktor K. Prasanna. fpl 2021: 404 [doi]

Monte Carlo Tree Search for Task Mapping onto Heterogeneous PlatformsTa-Yang Wang, William Chang, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna. hipc 2021: 63-70 [doi]

Programmable FPGA-based Memory ControllerSasindu Wijeratne, Sanket Pattnaik, ZhiYu Chen, Rajgopal Kannan, Viktor K. Prasanna. hoti 2021: 43-51 [doi]

Reconfigurable Low-latency Memory System for Sparse Matricized Tensor Times Khatri-Rao Product on FPGASasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna. hpec 2021: 1-7 [doi]

FPGA Acceleration of Number Theoretic TransformTian Ye, Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. supercomputer 2021: 98-117 [doi]

Performance Modeling and FPGA Acceleration of Homomorphic Encrypted ConvolutionTian Ye, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. fpl 2021: 115-121 [doi]

Decoupling the Depth and Scope of Graph Neural NetworksHanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen. nips 2021: 19665-19679 [doi]

Accurate, efficient and scalable training of Graph Neural NetworksHanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna. jpdc, 147:166-183, 2021. [doi]

BoostGCN: A Framework for Optimizing GCN Inference on FPGABingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna. fccm 2021: 29-39 [doi]

GenMAT: A General-Purpose Machine Learning-Driven Auto-Tuner for Heterogeneous PlatformsNaifeng Zhang, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna. sc 2021: 1-9 [doi]

A Framework for Optimizing GCN Inference on FPGABingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna. fpga 2021: 145 [doi]

Efficient Neighbor-Sampling-based GNN Training on CPU-FPGA Heterogeneous PlatformBingyi Zhang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. hpec 2021: 1-7 [doi]

BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement LearningChi Zhang, Sanmukh R. Kuppannagari, Viktor K. Prasanna. acml 2021: 204-219 [doi]

SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity EmbeddingsHongkuan Zhou, James Orme-Rogers, Rajgopal Kannan, Viktor K. Prasanna. CIKM 2021: 3667-3671 [doi]

Accelerating Large Scale Real-Time GNN Inference using Channel PruningHongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna. pvldb, 14(9):1597-1605, 2021. [doi]

2020

A High Throughput Parallel Hash Table on FPGA using XOR-based MemoryRuizhi Zhang 0002, Sasindu Wijeratne, Yang Yang, Sanmukh R. Kuppannagari, Viktor K. Prasanna. hpec 2020: 1-7 [doi]

Load Demand User Profiling in Smart Grids with Distributed Solar GenerationChung-Ming Cheung, Sanmukh Rao Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. isgt 2020: 1-5 [doi]

Crowdsourced Edge: A Novel Networking Paradigm for the Collaborative CommunityStéphane Kündig, Constantinos Marios Angelopoulos, Sanmukh R. Kuppannagari, José D. P. Rolim, Viktor K. Prasanna. dcoss 2020: 474-481 [doi]

How to Efficiently Train Your AI Agent? Characterizing and Evaluating Deep Reinforcement Learning on Heterogeneous PlatformsYuan Meng, Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna. hpec 2020: 1-7 [doi]

QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning AcceleratorsYuan Meng, Sanmukh R. Kuppannagari, Rachit Rajat, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna. ipps 2020: 107-114 [doi]

Accelerating Proximal Policy Optimization on CPU-FPGA Heterogeneous PlatformsYuan Meng, Sanmukh R. Kuppannagari, Viktor K. Prasanna. fccm 2020: 19-27 [doi]

Reuse Kernels or Activations?: A Flexible Dataflow for Low-latency Spectral CNN AccelerationYue Niu, Rajgopal Kannan, Ajitesh Srivastava, Viktor K. Prasanna. fpga 2020: 266-276 [doi]

QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning AcceleratorsRachit Rajat, Yuan Meng, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Viktor K. Prasanna, Rajgopal Kannan. fpga 2020: 323 [doi]

Towards High Performance, Portability, and Productivity: Lightweight Augmented Neural Networks for Performance PredictionAjitesh Srivastava, Naifeng Zhang, Rajgopal Kannan, Viktor K. Prasanna. hipc 2020: 21-30 [doi]

A Framework for Task Mapping onto Heterogeneous PlatformsTa-Yang Wang, Ajitesh Srivastava, Viktor K. Prasanna. hpec 2020: 1-6 [doi]

A High Throughput Parallel Hash Table Accelerator on HBM-enabled FPGAsYang Yang, Sanmukh R. Kuppannagari, Viktor K. Prasanna. icfpt 2020: 148-153 [doi]

FASTHash: FPGA-Based High Throughput Parallel Hash TableYang Yang, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna. supercomputer 2020: 3-22 [doi]

Accelerator Design and Performance Modeling for Homomorphic Encrypted CNN InferenceTian Ye, Rajgopal Kannan, Viktor K. Prasanna. hpec 2020: 1-7 [doi]

GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous PlatformsHanqing Zeng, Viktor K. Prasanna. fpga 2020: 255-265 [doi]

GraphSAINT: Graph Sampling Based Inductive Learning MethodHanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna. iclr 2020: [doi]

Accelerating Large Scale GCN Inference on FPGABingyi Zhang, Hanqing Zeng, Viktor K. Prasanna. fccm 2020: 241 [doi]

Hardware Acceleration of Large Scale GCN InferenceBingyi Zhang, Hanqing Zeng, Viktor K. Prasanna. asap 2020: 61-68 [doi]

RAOP: Recurrent Neural Network Augmented Offset PrefetcherPengmiao Zhang, Ajitesh Srivastava, Benjamin Brooks, Rajgopal Kannan, Viktor K. Prasanna. memsys 2020: 352-362 [doi]

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