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Virtual thread: maximizing thread-level parallelism beyond GPU scheduling limit by Myung Kuk Yoon; Keunsoo Kim; Sangpil Lee; Won Woo Ro; Murali Annavaram is a Computer Science article available to read on EtoBox.

What is Virtual thread: maximizing thread-level parallelism beyond GPU scheduling limit about?

Modern GPUs require tens of thousands of concurrent threads to fully utilize the massive amount of processing resources. However, thread concurrency in GPUs can be diminished either due to shortage of thread scheduling structures (scheduling limit), such as available program counters and single instruction multiple thread stacks, or due to shortage of on-chip memory (capacity limit), such as register file and shared memory. Our evaluations show that in practice concurrency in many general purpose applications running on GPUs is curtailed by the scheduling limit rather than the capacity limit. Maximizing the utilization of on-chip memory resources without unduly increasing the scheduling complexity is a key goal of this paper. This paper proposes a Virtual Thread (VT) architecture which assigns Cooperative Thread Arrays (CTAs) up to the capacity limit, while ignoring the scheduling limit. However, to reduce the logic complexity of managing more threads concurrently, we propose to place CTAs into active and inactive states, such that the number of active CTAs still respects the scheduling limit. When all the warps in an active CTA hit a long latency stall, the active CTA is context s

Who reads Virtual thread: maximizing thread-level parallelism beyond GPU scheduling limit?

Author

Myung Kuk Yoon; Keunsoo Kim; Sangpil Lee; Won Woo Ro; Murali Annavaram

Publisher

ACM

Published

2016

Language

EN

Field

Computer Science (Physical Sciences)