328 citations · 849 across the 44 of their papers we have counts for
8 papers · 1 filter
Dynasor: A Dynamic Memory Layout for Accelerating Sparse MTTKRP for Tensor Decomposition on Multi-core CPU
Sasindu Wijeratne, Rajgopal Kannan, Viktor Prasanna
Sparse Matricized Tensor Times Khatri-Rao Product (spMTTKRP) is the most time-consuming compute kernel in sparse tensor decomposition. In this paper, we introduce a novel algorithm…
Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform
Yuan Meng, Rajgopal Kannan, Viktor Prasanna
Monte Carlo Tree Search (MCTS) methods have achieved great success in many Artificial Intelligence (AI) benchmarks. The in-tree operations become a critical performance bottleneck…
Towards Programmable Memory Controller for Tensor Decomposition
Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan +1
Tensor decomposition has become an essential tool in many data science applications. Sparse Matricized Tensor Times Khatri-Rao Product (MTTKRP) is the pivotal kernel in tensor deco…
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…
DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference
Yuan Meng, Sanmukh Kuppannagari, Rajgopal Kannan +1
Most of the existing work on FPGA acceleration of Convolutional Neural Network (CNN) focus on employing a single strategy (algorithm, dataflow, etc.) across all the layers. Such an…
RECEIPT: REfine CoarsE-grained IndePendent Tasks for Parallel Tip decomposition of Bipartite Graphs
Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna +1
Tip decomposition is a crucial kernel for mining dense subgraphs in bipartite networks, with applications in spam detection, analysis of affiliation networks etc. It creates a hier…