6 citations · 9 across the 2 of their papers we have counts for
4 papers
PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses
Seung Won Min, Kun Wu, Sitao Huang +5
With the increasing adoption of graph neural networks (GNNs) in the machine learning community, GPUs have become an essential tool to accelerate GNN training. However, training GNN…
Tearing Down the Memory Wall
Zaid Qureshi, Vikram Sharma Mailthody, Seung Won Min +3
We present a vision for the Erudite architecture that redefines the compute and memory abstractions such that memory bandwidth and capacity become first-class citizens along with c…
EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal In GPUs
Seung Won Min, Vikram Sharma Mailthody, Zaid Qureshi +3
Modern analytics and recommendation systems are increasingly based on graph data that capture the relations between entities being analyzed. Practical graphs come in huge sizes, of…
Analysis and Optimization of I/O Cache Coherency Strategies for SoC-FPGA Device
Seung Won Min, Sitao Huang, Mohamed El-Hadedy +3
Unlike traditional PCIe-based FPGA accelerators, heterogeneous SoC-FPGA devices provide tighter integrations between software running on CPUs and hardware accelerators. Modern hete…