26 citations · 61 across the 17 of their papers we have counts for
19 papers
A Study of Mixed Precision Strategies for GMRES on GPUs
Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki +2
Support for lower precision computation is becoming more common in accelerator hardware due to lower power usage, reduced data movement and increased computational performance. How…
Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators
Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi +5
To meet the extreme compute demands for deep learning across commercial and scientific applications, dataflow accelerators are becoming increasingly popular. While these "domain-sp…
Parallel Graph Coloring Algorithms for Distributed GPU Environments
Ian Bogle, Erik G Boman, Karen D Devine +2
Graph coloring is often used in parallelizing scientific computations that run in distributed and multi-GPU environments; it identifies sets of independent data that can be updated…
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication
Gordon E. Moon, Hyoukjun Kwon, Geonhwa Jeong +3
There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via…
Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs
Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki +2
Support for lower precision computation is becoming more common in accelerator hardware due to lower power usage, reduced data movement and increased computational performance. How…
Sphynx: a parallel multi-GPU graph partitioner for distributed-memory systems
Seher Acer, Erik G Boman, Christian A Glusa +1
Graph partitioning has been an important tool to partition the work among several processors to minimize the communication cost and balance the workload. While accelerator-based su…