
Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery
Wing and Tip decomposition construct a hierarchy of butterflydense edge...
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Reconfigurable Lowlatency Memory System for Sparse Matricized Tensor Times KhatriRao Product on FPGA
Tensor decomposition has become an essential tool in many applications i...
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SeDyT: A General Framework for MultiStep Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings
Temporal Knowledge Graphs store events in the form of subjects, relation...
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Programmable FPGAbased Memory Controller
Even with generational improvements in DRAM technology, memory access la...
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Accelerating Large Scale RealTime GNN Inference using Channel Pruning
Graph Neural Networks (GNNs) are proven to be powerful models to generat...
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Deep Graph Neural Networks with Shallow Subgraph Samplers
While Graph Neural Networks (GNNs) are powerful models for learning repr...
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DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference
Most of the existing works on FPGA acceleration of Convolutional Neural ...
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RECEIPT: REfine CoarsEgrained IndePendent Tasks for Parallel Tip decomposition of Bipartite Graphs
Tip decomposition is a crucial kernel for mining dense subgraphs in bipa...
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Accurate, Efficient and Scalable Training of Graph Neural Networks
Graph Neural Networks (GNNs) are powerful deep learning models to genera...
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GraphACT: Accelerating GCN Training on CPUFPGA Heterogeneous Platforms
Graph Convolutional Networks (GCNs) have emerged as the stateoftheart...
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SPEC2: SPECtral SParsE CNN Accelerator on FPGAs
To accelerate inference of Convolutional Neural Networks (CNNs), various...
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GraphSAINT: Graph Sampling Based Inductive Learning Method
Graph Convolutional Networks (GCNs) are powerful models for learning rep...
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Planting Trees for scalable and efficient Canonical Hub Labeling
PointtoPoint Shortest Distance (PPSD) query is a crucial primitive in ...
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Accurate, Efficient and Scalable Graph Embedding
The Graph Convolutional Network (GCN) model and its variants are powerfu...
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GPOP: A cache and workefficient framework for Graph Processing Over Partitions
The past decade has seen development of many sharedmemory graph process...
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Accelerating PageRank using PartitionCentric Processing
PageRank is a fundamental link analysis algorithm and a key representati...
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Viktor Prasanna
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