2 citations · 5 across the 5 of their papers we have counts for
5 papers
Entropy Aware Training for Fast and Accurate Distributed GNN
Dhruv Deshmukh, Gagan Raj Gupta, Manisha Chawla +2
Several distributed frameworks have been developed to scale Graph Neural Networks (GNNs) on billion-size graphs. On several benchmarks, we observe that the graph partitions generat…
An Adaptive Load Balancer For Graph Analytical Applications on GPUs
Vishwesh Jatala, Loc Hoang, Roshan Dathathri +3
Load-balancing among the threads of a GPU for graph analytics workloads is difficult because of the irregular nature of graph applications and the high variability in vertex degree…
GREENER: A Tool for Improving Energy Efficiency of Register Files
Vishwesh Jatala, Jayvant Anantpur, Amey Karkare
Graphics Processing Units (GPUs) maintain a large register file to increase the thread level parallelism (TLP). To increase the TLP further, recent GPUs have increased the number o…
Scratchpad Sharing in GPUs
Vishwesh Jatala, Jayvant Anantpur, Amey Karkare
GPGPU applications exploit on-chip scratchpad memory available in the Graphics Processing Units (GPUs) to improve performance. The amount of thread level parallelism present in the…
Improving GPU Performance Through Resource Sharing
Vishwesh Jatala, Jayvant Anantpur, Amey Karkare
Graphics Processing Units (GPUs) consisting of Streaming Multiprocessors (SMs) achieve high throughput by running a large number of threads and context switching among them to hide…