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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
- 2024
[j182]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)- [j181]Yi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna:
HitGNN: High-Throughput GNN Training Framework on CPU+Multi-FPGA Heterogeneous Platform. IEEE Trans. Parallel Distributed Syst. 35(5): 707-719 (2024) - [c588]Yang Yang, Rajgopal Kannan, Viktor K. Prasanna:
A Framework for Generating Accelerators for Homomorphic Encryption Operations on FPGAs. ASAP 2024: 61-70 - [c587]Neelesh Gupta, Narayanan Kannan, Pengmiao Zhang, Viktor K. Prasanna:
TabConv: Low-Computation CNN Inference via Table Lookups. CF 2024 - [c586]Yi-Chien Lin, Gangda Deng, Viktor K. Prasanna:
A Unified CPU-GPU Protocol for GNN Training. CF 2024 - [c585]Yuan Meng, Michael Kinsner, Deshanand P. Singh, Mahesh A. Iyer, Viktor K. Prasanna:
PEARL: Enabling Portable, Productive, and High-Performance Deep Reinforcement Learning using Heterogeneous Platforms. CF 2024 - [c584]Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna:
Sparse MTTKRP Acceleration for Tensor Decomposition on GPU. CF 2024 - [c583]Zhihan Xu, Yang Yang, Rajgopal Kannan, Viktor K. Prasanna:
Bandwidth Efficient Homomorphic Encrypted Discrete Fourier Transform Acceleration on FPGA. FCCM 2024: 1-12 - [c582]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 - [c581]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 - [c580]Jürgen Becker, Zhenman Fang, Viktor K. Prasanna, Marco D. Santambrogio, Ramachandran Vaidyanathan:
31st Reconfigurable Architectures Workshop (RAW 2024). IPDPS (Workshops) 2024: 79 - [c579]Yi-Chien Lin, Yuyang Chen, Sameh Gobriel, Nilesh Jain, Gopi Krishna Jha, Viktor K. Prasanna:
ARGO: An Auto-Tuning Runtime System for Scalable GNN Training on Multi-Core Processor. IPDPS 2024: 361-372 - [c578]Pengmiao Zhang, Neelesh Gupta, Rajgopal Kannan, Viktor K. Prasanna:
Attention, Distillation, and Tabularization: Towards Practical Neural Network-Based Prefetching. IPDPS 2024: 876-888 - [c577]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 - [i79]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) - [i78]Pengmiao Zhang, Neelesh Gupta, Rajgopal Kannan, Viktor K. Prasanna:
Attention, Distillation, and Tabularization: Towards Practical Neural Network-Based Prefetching. CoRR abs/2401.06362 (2024) - [i77]Yi-Chien Lin, Yuyang Chen, Sameh Gobriel, Nilesh Jain, Gopi Krishna Jha, Viktor K. Prasanna:
ARGO: An Auto-Tuning Runtime System for Scalable GNN Training on Multi-Core Processor. CoRR abs/2402.03671 (2024) - [i76]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) - [i75]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) - [i74]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) - [i73]Yi-Chien Lin, Gangda Deng, Viktor K. Prasanna:
A Unified CPU-GPU Protocol for GNN Training. CoRR abs/2403.17092 (2024) - [i72]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) - [i71]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) - [i70]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) - [i69]Neelesh Gupta, Narayanan Kannan, Pengmiao Zhang, Viktor K. Prasanna:
TabConv: Low-Computation CNN Inference via Table Lookups. CoRR abs/2404.05872 (2024) - [i68]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) - [i67]Sasindu Wijeratne, Rajgopal Kannan, Viktor K. Prasanna:
Sparse MTTKRP Acceleration for Tensor Decomposition on GPU. CoRR abs/2405.08470 (2024) - [i66]Zuoning Zhang, Dhruv Parikh, Youning Zhang, Viktor K. Prasanna:
Benchmarking the Performance of Large Language Models on the Cerebras Wafer Scale Engine. CoRR abs/2409.00287 (2024) - [i65]Jacob Fein-Ashley, Rajgopal Kannan, Viktor K. Prasanna:
Studying the Effects of Self-Attention on SAR Automatic Target Recognition. CoRR abs/2409.00473 (2024) - [i64]Gangda Deng, Hongkuan Zhou, Rajgopal Kannan, Viktor K. Prasanna:
Learning Personalized Scoping for Graph Neural Networks under Heterophily. CoRR abs/2409.06998 (2024) - 2023
- [j180]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) - [j179]Chi Zhang, Yuan Meng, Viktor K. Prasanna:
A Framework for Mapping DRL Algorithms With Prioritized Replay Buffer Onto Heterogeneous Platforms. IEEE Trans. Parallel Distributed Syst. 34(6): 1816-1829 (2023) - [j178]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
GraphAGILE: An FPGA-Based Overlay Accelerator for Low-Latency GNN Inference. IEEE Trans. Parallel Distributed Syst. 34(9): 2580-2597 (2023) - [j177]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) - [c576]Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Training Heterogeneous Graph Neural Networks using Bandit Sampling. CIKM 2023: 4345-4349 - [c575]Samuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Characterizing Speed Performance of Multi-Agent Reinforcement Learning. DATA 2023: 327-334 - [c574]Yi-Chien Lin, Viktor K. Prasanna:
A Framework for Graph Machine Learning on Heterogeneous Architecture. FCCM 2023: 245-246 - [c573]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 - [c572]Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Sparse MTTKRP for Tensor Decomposition on FPGA. FPGA 2023: 259-269 - [c571]Yang Yang, Weihang Long, Rajgopal Kannan, Viktor K. Prasanna:
FPGA Acceleration of Rotation in Homomorphic Encryption Using Dynamic Data Layout. FPL 2023: 174-181 - [c570]Paul Chen, Pavan Manjunath, Sasindu Wijeratne, Bingyi Zhang, Viktor K. Prasanna:
Exploiting On-Chip Heterogeneity of Versal Architecture for GNN Inference Acceleration. FPL 2023: 219-227 - [c569]Kyle Marino, Pengmiao Zhang, Viktor K. Prasanna:
ME- ViT: A Single-Load Memory-Efficient FPGA Accelerator for Vision Transformers. HiPC 2023: 213-223 - [c568]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 - [c567]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 - [c566]Neelesh Gupta, Pengmiao Zhang, Rajgopal Kannan, Viktor K. Prasanna:
PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Models. HPEC 2023: 1-7 - [c565]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 - [c564]Samuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Multi-Agent DDPG on CPU-FPGA Heterogeneous Platform. HPEC 2023: 1-7 - [c563]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 - [c562]Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna:
HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN. INFOCOM 2023: 1-10 - [c561]Bingyi Zhang, Viktor K. Prasanna:
Dynasparse: Accelerating GNN Inference through Dynamic Sparsity Exploitation. IPDPS 2023: 233-244 - [c560]Yi-Chien Lin, Viktor K. Prasanna:
HyScale-GNN: A Scalable Hybrid GNN Training System on Single-Node Heterogeneous Architecture. IPDPS 2023: 557-567 - [c559]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 - [c558]Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna:
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. SC 2023: 39:1-39:12 - [c557]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 - [c556]Yuan Meng, Qian Wang, Tianxin Zu, Viktor K. Prasanna:
Accelerating Deep Neural Network guided MCTS using Adaptive Parallelism. SC Workshops 2023: 766-769 - [c555]Gangda Deng, Ömer Faruk Akgül, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Jianbo Li, Viktor K. Prasanna:
An Efficient Distributed Graph Engine for Deep Learning on Graphs. SC Workshops 2023: 922-931 - [i63]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) - [i62]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
GraphAGILE: An FPGA-based Overlay Accelerator for Low-latency GNN Inference. CoRR abs/2302.01769 (2023) - [i61]Yi-Chien Lin, Viktor K. Prasanna:
HyScale-GNN: A Scalable Hybrid GNN Training System on Single-Node Heterogeneous Architecture. CoRR abs/2303.00158 (2023) - [i60]Yi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna:
HitGNN: High-throughput GNN Training Framework on CPU+Multi-FPGA Heterogeneous Platform. CoRR abs/2303.01568 (2023) - [i59]Bingyi Zhang, Viktor K. Prasanna:
Dynasparse: Accelerating GNN Inference through Dynamic Sparsity Exploitation. CoRR abs/2303.12901 (2023) - [i58]Hongkuan Zhou, Rajgopal Kannan, Ananthram Swami, Viktor K. Prasanna:
HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN. CoRR abs/2304.10013 (2023) - [i57]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) - [i56]Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna:
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. CoRR abs/2307.07649 (2023) - [i55]Paul Chen, Pavan Manjunath, Sasindu Wijeratne, Bingyi Zhang, Viktor K. Prasanna:
Exploiting On-chip Heterogeneity of Versal Architecture for GNN Inference Acceleration. CoRR abs/2308.02749 (2023) - [i54]Samuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Characterizing Speed Performance of Multi-Agent Reinforcement Learning. CoRR abs/2309.07108 (2023) - [i53]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) - [i52]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) - [i51]Yuan Meng, Qian Wang, Tianxin Zu, Viktor K. Prasanna:
Accelerating Deep Neural Network guided MCTS using Adaptive Parallelism. CoRR abs/2310.05313 (2023) - [i50]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) - [i49]Yuan Meng, Michael Kinsner, Deshanand P. Singh, Mahesh A. Iyer, Viktor K. Prasanna:
A Software-Hardware Co-Optimized Toolkit for Deep Reinforcement Learning on Heterogeneous Platforms. CoRR abs/2311.09445 (2023) - [i48]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) - [i47]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
- [j176]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) - [j175]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) - [j174]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) - [j173]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) - [j172]Ken Eguro, Stephen Neuendorffer, Viktor K. Prasanna, Hongbo Rong:
Introduction to Special Issue on FPGAs in Data Centers, Part II. ACM Trans. Reconfigurable Technol. Syst. 15(3): 22:1-22:2 (2022) - [j171]Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K. Prasanna:
Safe Building HVAC Control via Batch Reinforcement Learning. IEEE Trans. Sustain. Comput. 7(4): 923-934 (2022) - [c554]Diyi Hu, Chi Zhang, Viktor K. Prasanna, Bhaskar Krishnamachari:
Learning Practical Communication Strategies in Cooperative Multi-Agent Reinforcement Learning. ACML 2022: 467-482 - [c553]Diyi Hu, Chi Zhang, Viktor K. Prasanna, Bhaskar Krishnamachari:
Intelligent Communication over Realistic Wireless Networks in Multi-Agent Cooperative Games. AAMAS 2022: 1627-1629 - [c552]Yi-Chien Lin, Bingyi Zhang, Viktor K. Prasanna:
Accelerating GNN Training on CPU+Multi-FPGA Heterogeneous Platform. CARLA 2022: 16-30 - [c551]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 - [c550]Yuan Meng, Chi Zhang, Viktor K. Prasanna:
FPGA acceleration of deep reinforcement learning using on-chip replay management. CF 2022: 40-48 - [c549]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 - [c548]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 - [c547]Pengmiao Zhang, Rajgopal Kannan, Anant V. Nori, Viktor K. Prasanna:
A2P: Attention-based Memory Access Prediction for Graph Analytics. DATA 2022: 135-145 - [c546]Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Towards Programmable Memory Controller for Tensor Decomposition. DATA 2022: 468-475 - [c545]Yuan Meng, Hongjiang Men, Viktor K. Prasanna:
Accelerating Deformable Convolution Networks. FCCM 2022: 1 - [c544]Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
FPGA Accelerator for Homomorphic Encrypted Sparse Convolutional Neural Network Inference. FCCM 2022: 1-9 - [c543]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
End-to-End Acceleration of Homomorphic Encrypted CNN Inference on FPGAs. FPGA 2022: 51 - [c542]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 - [c541]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
DecGNN: A Framework for Mapping Decoupled GNN Models onto CPU-FPGA Heterogeneous Platform. FPGA 2022: 154 - [c540]Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart:
Accurate, Low-latency, Efficient SAR Automatic Target Recognition on FPGA. FPL 2022: 1-8 - [c539]Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform. FPL 2022: 176-182 - [c538]Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna:
Bandwidth Efficient Homomorphic Encrypted Matrix Vector Multiplication Accelerator on FPGA. FPT 2022: 1-9 - [c537]Soundarya Jayaraman, Bingyi Zhang, Viktor K. Prasanna:
Hypersort: High-performance Parallel Sorting on HBM-enabled FPGA. FPT 2022: 1-11 - [c536]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
Low-latency Mini-batch GNN Inference on CPU-FPGA Heterogeneous Platform. HIPC 2022: 11-21 - [c535]Kartik Lakhotia, Fabrizio Petrini, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Prefix Scan with in-network computing on Intel PIUMA. HIPC 2022: 59-68 - [c534]Jason Yik, Sanmukh R. Kuppannagari, Hanqing Zeng, Viktor K. Prasanna:
Input Feature Pruning for Accelerating GNN Inference on Heterogeneous Platforms. HIPC 2022: 282-291 - [c533]Sasindu Wijeratne, Akhilesh R. Jaiswal, Ajey P. Jacob, Bingyi Zhang, Viktor K. Prasanna:
Performance Modeling Sparse MTTKRP Using Optical Static Random Access Memory on FPGA. HPEC 2022: 1-7 - [c532]Tian Ye, Rajgopal Kannan, Viktor K. Prasanna:
FPGA Acceleration of Fully Homomorphic Encryption over the Torus. HPEC 2022: 1-7 - [c531]Bingyi Zhang, Akhilesh R. Jaiswal, Clynn Mathew, Ravi Teja Lakkireddy, Ajey P. Jacob, Sasindu Wijeratne, Viktor K. Prasanna:
Modeling the Energy Efficiency of GEMM using Optical Random Access Memory. HPEC 2022: 1-7 - [c530]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 - [c529]Haomei Liu, Yuan Meng, Sanmukh Rao Kuppannagari, Viktor K. Prasanna:
End to End Framework for CNN Acceleration on FPGAs with Dynamic Algorithm Mapping. IC3 2022: 696-700 - [c528]Jürgen Becker, Lana Josipovic, Viktor K. Prasanna, Marco D. Santambrogio, Ramachandran Vaidyanathan:
29th Reconfigurable Architectures Workshop (RAW 2022). IPDPS Workshops 2022: 65-66 - [c527]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 - [c526]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 - [c525]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 - [c524]Yuan Meng, Hongjiang Men, Viktor K. Prasanna:
Accelerator Design and Exploration for Deformable Convolution Networks. SiPS 2022: 1-6 - [p3]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
Computational Models for Cascades in Massive Graphs. Massive Graph Analytics 2022: 377-395 - [i46]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) - [i45]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) - [i44]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) - [i43]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) - [i42]Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna:
TransforMAP: Transformer for Memory Access Prediction. CoRR abs/2205.14778 (2022) - [i41]Bingyi Zhang, Hanqing Zeng, Viktor K. Prasanna:
Low-latency Mini-batch GNN Inference on CPU-FPGA Heterogeneous Platform. CoRR abs/2206.08536 (2022) - [i40]Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor K. Prasanna:
Towards Programmable Memory Controller for Tensor Decomposition. CoRR abs/2207.08298 (2022) - [i39]