328 citations · 1.2k across the 57 of their papers we have counts for
10 papers · 1 filter
HP-GNN: Generating High Throughput GNN Training Implementation on CPU-FPGA Heterogeneous Platform
Yi-Chien Lin, Bingyi Zhang, Viktor Prasanna
Graph Neural Networks (GNNs) have shown great success in many applications such as recommendation systems, molecular property prediction, traffic prediction, etc. Recently, CPU-FPG…
Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery
Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna
Wing and Tip decomposition construct a hierarchy of butterfly-dense edge and vertex induced bipartite subgraphs, respectively. They have applications in several domains including e…
BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement Learning
Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K Prasanna
Online interactions with the environment to collect data samples for training a Reinforcement Learning (RL) agent is not always feasible due to economic and safety concerns. The go…
Parallel Actors and Learners: A Framework for Generating Scalable RL Implementations
Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K Prasanna
Reinforcement Learning (RL) has achieved significant success in application domains such as robotics, games and health care. However, training RL agents is very time consuming. Cur…
Reconfigurable Low-latency Memory System for Sparse Matricized Tensor Times Khatri-Rao Product on FPGA
Sasindu Wijeratne, Rajgopal Kannan, Viktor Prasanna
Tensor decomposition has become an essential tool in many applications in various domains, including machine learning. Sparse Matricized Tensor Times Khatri-Rao Product (MTTKRP) is…
SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings
Hongkuan Zhou, James Orme-Rogers, Rajgopal Kannan +1
Temporal Knowledge Graphs store events in the form of subjects, relations, objects, and timestamps which are often represented by dynamic heterogeneous graphs. Event forecasting is…
Programmable FPGA-based Memory Controller
Sasindu Wijeratne, Sanket Pattnaik, Zhiyu Chen +2
Even with generational improvements in DRAM technology, memory access latency still remains the major bottleneck for application accelerators, primarily due to limitations in memor…
A High Throughput Parallel Hash Table on FPGA using XOR-based Memory
Ruizhi Zhang, Sasindu Wijeratne, Yang Yang +2
Hash table is a fundamental data structure for quick search and retrieval of data. It is a key component in complex graph analytics and AI/ML applications. State-of-the-art paralle…
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning
Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng +2
Graph Neural Networks (GNNs) are proven to be powerful models to generate node embedding for downstream applications. However, due to the high computation complexity of GNN inferen…
The EpiBench Platform to Propel AI/ML-based Epidemic Forecasting: A Prototype Demonstration Reaching Human Expert-level Performance
Ajitesh Srivastava, Tianjian Xu, Viktor K. Prasanna
During the COVID-19 pandemic, a significant effort has gone into developing ML-driven epidemic forecasting techniques. However, benchmarks do not exist to claim if a new AI/ML tech…