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2020 – today
- 2024
[j48]Pengmiao Zhang
, Rajgopal Kannan, Anant V. Nori, Viktor K. Prasanna:
Accelerating Graph Analytics Using Attention-Based Data Prefetcher. SN Comput. Sci. 5(5): 646 (2024)- [j47]Bingyi Zhang, Rajgopal Kannan, Carl E. Busart, Viktor K. Prasanna:
VisionAGILE: A Versatile Domain-Specific Accelerator for Computer Vision Tasks. IEEE Trans. Parallel Distributed Syst. 35(12): 2405-2422 (2024) - [c137]Yang Yang, Rajgopal Kannan, Viktor K. Prasanna:
A Framework for Generating Accelerators for Homomorphic Encryption Operations on FPGAs. ASAP 2024: 61-70 - [c136]Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna:
Sparse MTTKRP Acceleration for Tensor Decomposition on GPU. CF 2024 - [c135]Zhihan Xu, Yang Yang, Rajgopal Kannan, Viktor K. Prasanna:
Bandwidth Efficient Homomorphic Encrypted Discrete Fourier Transform Acceleration on FPGA. FCCM 2024: 1-12 - [c134]Bingyi Zhang, Rajgopal Kannan, Carl E. Busart, Viktor K. Prasanna:
GCV-Turbo: End-to-end Acceleration of GNN-based Computer Vision Tasks on FPGA. FCCM 2024: 66-77 - [c133]Dhruv Parikh, Shouyi Li, Bingyi Zhang, Rajgopal Kannan, Carl E. Busart, Viktor K. Prasanna:
Accelerating ViT Inference on FPGA through Static and Dynamic Pruning. FCCM 2024: 78-89 - [c132]Pengmiao Zhang, Neelesh Gupta, Rajgopal Kannan, Viktor K. Prasanna:
Attention, Distillation, and Tabularization: Towards Practical Neural Network-Based Prefetching. IPDPS 2024: 876-888 - [c131]Gangda Deng, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Christopher Leung, Jianbo Li, Rajgopal Kannan, Viktor K. Prasanna:
TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. IPDPS 2024: 926-937 - [i59]Sasindu Wijeratne, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
PAHD: Perception-Action based Human Decision Making using Explainable Graph Neural Networks on SAR Images. CoRR abs/2401.02687 (2024) - [i58]Pengmiao Zhang, Neelesh Gupta, Rajgopal Kannan, Viktor K. Prasanna:
Attention, Distillation, and Tabularization: Towards Practical Neural Network-Based Prefetching. CoRR abs/2401.06362 (2024) - [i57]Gangda Deng, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Christopher Leung, Jianbo Li, Rajgopal Kannan, Viktor K. Prasanna:
TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. CoRR abs/2402.05396 (2024) - [i56]Neelesh Gupta, Pengmiao Zhang, Rajgopal Kannan, Viktor K. Prasanna:
PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Models. CoRR abs/2402.13441 (2024) - [i55]Dhruv Parikh, Shouyi Li, Bingyi Zhang, Rajgopal Kannan, Carl E. Busart, Viktor K. Prasanna:
Accelerating ViT Inference on FPGA through Static and Dynamic Pruning. CoRR abs/2403.14047 (2024) - [i54]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Uncertainty-Aware SAR ATR: Defending Against Adversarial Attacks via Bayesian Neural Networks. CoRR abs/2403.18318 (2024) - [i53]Xu Wang, Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
FACTUAL: A Novel Framework for Contrastive Learning Based Robust SAR Image Classification. CoRR abs/2404.03225 (2024) - [i52]Sachini Wickramasinghe, Dhruv Parikh, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
VTR: An Optimized Vision Transformer for SAR ATR Acceleration on FPGA. CoRR abs/2404.04527 (2024) - [i51]Bingyi Zhang, Rajgopal Kannan, Carl E. Busart, Viktor K. Prasanna:
GCV-Turbo: End-to-end Acceleration of GNN-based Computer Vision Tasks on FPGA. CoRR abs/2404.07188 (2024) - [i50]Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna:
Sparse MTTKRP Acceleration for Tensor Decomposition on GPU. CoRR abs/2405.08470 (2024) - [i49]Jacob Fein-Ashley, Rajgopal Kannan, Viktor K. Prasanna:
Studying the Effects of Self-Attention on SAR Automatic Target Recognition. CoRR abs/2409.00473 (2024) - [i48]Gangda Deng, Hongkuan Zhou, Rajgopal Kannan, Viktor K. Prasanna:
Learning Personalized Scoping for Graph Neural Networks under Heterophily. CoRR abs/2409.06998 (2024) - [i47]Ömer Faruk Akgül, Rajgopal Kannan, Viktor K. Prasanna:
Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information. CoRR abs/2410.14010 (2024) - [i46]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
Adversarial Training in Low-Label Regimes with Margin-Based Interpolation. CoRR abs/2411.17959 (2024) - 2023
- [j46]Tian Xie, Rajgopal Kannan, C.-C. Jay Kuo:
Label Efficient Regularization and Propagation for Graph Node Classification. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14856-14871 (2023) - [j45]Kartik Lakhotia, Rajgopal Kannan, Viktor K. Prasanna:
Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery. ACM Trans. Parallel Comput. 10(2): 5:1-5:35 (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) - [c130]Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Training Heterogeneous Graph Neural Networks using Bandit Sampling. CIKM 2023: 4345-4349 - [c129]Samuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Characterizing Speed Performance of Multi-Agent Reinforcement Learning. DATA 2023: 327-334 - [c128]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 - [c127]Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Sparse MTTKRP for Tensor Decomposition on FPGA. FPGA 2023: 259-269 - [c126]Yang Yang, Weihang Long, Rajgopal Kannan, Viktor K. Prasanna:
FPGA Acceleration of Rotation in Homomorphic Encryption Using Dynamic Data Layout. FPL 2023: 174-181 - [c125]Jacob Fein-Ashley, Tian Ye, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Benchmarking Deep Learning Classifiers for SAR Automatic Target Recognition. HPEC 2023: 1-6 - [c124]Abhiram Rao Gorle, Pengmiao Zhang, Rajgopal Kannan, Viktor K. Prasanna:
G-MAP: A Graph Neural Network-Based Framework for Memory Access Prediction. HPEC 2023: 1-7 - [c123]Neelesh Gupta, Pengmiao Zhang, Rajgopal Kannan, Viktor K. Prasanna:
PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Models. HPEC 2023: 1-7 - [c122]Dhruv Parikh, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Performance of Graph Neural Networks for Point Cloud Applications. HPEC 2023: 1-7 - [c121]Samuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Multi-Agent DDPG on CPU-FPGA Heterogeneous Platform. HPEC 2023: 1-7 - [c120]Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Accelerating GNN-Based SAR Automatic Target Recognition on HBM-Enabled FPGA. HPEC 2023: 1-7 - [c119]Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna:
HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN. INFOCOM 2023: 1-10 - [c118]Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna:
Dynasor: A Dynamic Memory Layout for Accelerating Sparse MTTKRP for Tensor Decomposition on Multi-core CPU. SBAC-PAD 2023: 23-33 - [c117]Pengmiao Zhang, Rajgopal Kannan, Viktor K. Prasanna:
Phases, Modalities, Spatial and Temporal Locality: Domain Specific ML Prefetcher for Accelerating Graph Analytics. SC 2023: 91:1-91:15 - [i45]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) - [i44]Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna:
HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN. CoRR abs/2304.10013 (2023) - [i43]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) - [i42]Samuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Characterizing Speed Performance of Multi-Agent Reinforcement Learning. CoRR abs/2309.07108 (2023) - [i41]Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna:
Dynasor: A Dynamic Memory Layout for Accelerating Sparse MTTKRP for Tensor Decomposition on Multi-core CPU. CoRR abs/2309.09131 (2023) - [i40]Dhruv Parikh, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Performance of Graph Neural Networks for Point Cloud Applications. CoRR abs/2309.09142 (2023) - [i39]Yue Niu, Rajgopal Kannan, Ajitesh Srivastava, Viktor K. Prasanna:
Reuse Kernels or Activations? A Flexible Dataflow for Low-latency Spectral CNN Acceleration. CoRR abs/2310.10902 (2023) - [i38]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart, Lance M. Kaplan:
Realistic Scatterer Based Adversarial Attacks on SAR Image Classifiers. CoRR abs/2312.02912 (2023) - [i37]Jacob Fein-Ashley, Tian Ye, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Benchmarking Deep Learning Classifiers for SAR Automatic Target Recognition. CoRR abs/2312.06940 (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) - [c116]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 - [c115]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 - [c114]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 - [c113]Pengmiao Zhang, Rajgopal Kannan, Anant V. Nori, Viktor K. Prasanna:
A2P: Attention-based Memory Access Prediction for Graph Analytics. DATA 2022: 135-145 - [c112]Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Towards Programmable Memory Controller for Tensor Decomposition. DATA 2022: 468-475 - [c111]Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
FPGA Accelerator for Homomorphic Encrypted Sparse Convolutional Neural Network Inference. FCCM 2022: 1-9 - [c110]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
End-to-End Acceleration of Homomorphic Encrypted CNN Inference on FPGAs. FPGA 2022: 51 - [c109]Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Accurate, Low-latency, Efficient SAR Automatic Target Recognition on FPGA. FPL 2022: 1-8 - [c108]Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform. FPL 2022: 176-182 - [c107]Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Bandwidth Efficient Homomorphic Encrypted Matrix Vector Multiplication Accelerator on FPGA. FPT 2022: 1-9 - [c106]Kartik Lakhotia, Fabrizio Petrini, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Prefix Scan with in-network computing on Intel PIUMA. HIPC 2022: 59-68 - [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 - [i36]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) - [i35]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) - [i34]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) - [i33]Tian Xie, Rajgopal Kannan, C.-C. Jay Kuo:
GraphHop++: New Insights into GraphHop and Its Enhancement. CoRR abs/2204.08646 (2022) - [i32]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) - [i31]Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna:
TransforMAP: Transformer for Memory Access Prediction. CoRR abs/2205.14778 (2022) - [i30]Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Towards Programmable Memory Controller for Tensor Decomposition. CoRR abs/2207.08298 (2022) - [i29]Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform. CoRR abs/2208.11208 (2022) - [i28]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 - [i27]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) - [i26]Sasindu Wijeratne, Sanket Pattnaik, Zhiyu Chen, Rajgopal Kannan, Viktor K. Prasanna:
Programmable FPGA-based Memory Controller. CoRR abs/2108.09601 (2021) - [i25]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) - [i24]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) - [i23]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 - [i22]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) - [i21]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) - [i20]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) - [i19]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)
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]