NDLI: On-the-fly elimination of dynamic irregularities for GPU computing (CARN, Vol. 39, Issue. 1)

Content Provider	ACM Digital Library
Author	Guo, Ziyu Jiang, Yunlian Tian, Kai Zhang, Eddy Z. Shen, Xipeng
Abstract	The power-efficient massively parallel Graphics Processing Units (GPUs) have become increasingly influential for general-purpose computing over the past few years. However, their efficiency is sensitive to dynamic irregular memory references and control flows in an application. Experiments have shown great performance gains when these irregularities are removed. But it remains an open question how to achieve those gains through software approaches on modern GPUs. This paper presents a systematic exploration to tackle dynamic irregularities in both control flows and memory references. It reveals some properties of dynamic irregularities in both control flows and memory references, their interactions, and their relations with program data and threads. It describes several heuristics-based algorithms and runtime adaptation techniques for effectively removing dynamic irregularities through data reordering and job swapping. It presents a framework, G-Streamline, as a unified software solution to dynamic irregularities in GPU computing. G-Streamline has several distinctive properties. It is a pure software solution and works on the fly, requiring no hardware extensions or offline profiling. It treats both types of irregularities at the same time in a holistic fashion, maximizing the whole-program performance by resolving conflicts among optimizations. Its optimization overhead is largely transparent to GPU kernel executions, jeopardizing no basic efficiency of the GPU application. Finally, it is robust to the presence of various complexities in GPU applications. Experiments show that G-Streamline is effective in reducing dynamic irregularities in GPU computing, producing speedups between 1.07 and 2.5 for a variety of applications.
Starting Page	369
Ending Page	380
Page Count	12
File Format	PDF
ISSN	01635964
DOI	10.1145/1961295.1950408
Journal	ACM SIGARCH Computer Architecture News (CARN)
Volume Number	39
Issue Number	1
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1981-04-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Memory coalescing Thread data remapping Thread divergence Data transformation Cpu-gpu pipelining Gpgpu
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

On-the-fly elimination of dynamic irregularities for GPU computing

On-the-fly elimination of dynamic irregularities for GPU computing (SIGP, Vol. 46, Issue. 3)

Streamlining GPU applications on the fly: thread divergence elimination through runtime thread-data remapping

A study towards optimal data layout for GPU computing

Streamlining GPU applications on the fly: thread divergence elimination through runtime thread-data remapping (2010)

Complexity analysis and algorithm design for reorganizing data to minimize non-coalesced memory accesses on GPU

Complexity analysis and algorithm design for reorganizing data to minimize non-coalesced memory accesses on GPU

A case for neuromorphic ISAs (CARN, Vol. 39, Issue. 1)

Dynamic knobs for responsive power-aware computing (CARN, Vol. 39, Issue. 1)

On-the-fly elimination of dynamic irregularities for GPU computing (CARN, Vol. 39, Issue. 1)

Similar Documents

On-the-fly elimination of dynamic irregularities for GPU computing

On-the-fly elimination of dynamic irregularities for GPU computing (SIGP, Vol. 46, Issue. 3)

Streamlining GPU applications on the fly: thread divergence elimination through runtime thread-data remapping

A study towards optimal data layout for GPU computing

Streamlining GPU applications on the fly: thread divergence elimination through runtime thread-data remapping (2010)

Complexity analysis and algorithm design for reorganizing data to minimize non-coalesced memory accesses on GPU

Complexity analysis and algorithm design for reorganizing data to minimize non-coalesced memory accesses on GPU

A case for neuromorphic ISAs (CARN, Vol. 39, Issue. 1)

Dynamic knobs for responsive power-aware computing (CARN, Vol. 39, Issue. 1)

On-the-fly elimination of dynamic irregularities for GPU computing (CARN, Vol. 39, Issue. 1)