NDLI: Eliminating redundant fragment shader executions on a mobile GPU via hardware memoization

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Unifying on-chip and inter-node switching within the Anton 2 network

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A low power and reliable charge pump design for phase change memories

Eliminating redundant fragment shader executions on a mobile GPU via hardware memoization

Real-world design and evaluation of compiler-managed GPU redundant multithreading

Harnessing ISA diversity

Going vertical in memory management

Replay debugging

Improving the energy efficiency of big cores

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Volume 42, Issue 1, March 2014

Eliminating redundant fragment shader executions on a mobile GPU via hardware memoization

Content Provider	ACM Digital Library
Author	Xekalakis, Polychronis Arnau, Jose-Maria Parcerisa, Joan-Manuel
Abstract	Redundancy is at the heart of graphical applications. In fact, generating an animation typically involves the succession of extremely similar images. In terms of rendering these images, this behavior translates into the creation of many fragment programs with the exact same input data. We have measured this fragment redundancy for a set of commercial Android applications, and found that more than 40% of the fragments used in a frame have been already computed in a prior frame. In this paper we try to exploit this redundancy, using fragment memoization. Unfortunately, this is not an easy task as most of the redundancy exists across frames, rendering most HW based schemes unfeasible. We thus first take a step back and try to analyze the temporal locality of the redundant fragments, their complexity, and the number of inputs typically seen in fragment programs. The result of our analysis is a task level memoization scheme, that easily outperforms the current state-of-the-art in low power GPUs More specifically, our experimental results show that our scheme is able to remove 59.7% of the redundant fragment computations on average. This materializes to a significant speedup of 17.6% on average, while also improving the overall energy efficiency by 8.9% on average.
Starting Page	529
Ending Page	540
Page Count	12
File Format	PDF
ISSN	01635964
DOI	10.1145/2678373.2665748
Journal	ACM SIGARCH Computer Architecture News (CARN)
Volume Number	42
Issue Number	3
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1981-04-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Content Type	Text
Resource Type	Article

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