Skip to main navigation
Skip to search
Skip to main content
Illinois Experts Home
LOGIN & Help
Link opens in a new tab
Search content at Illinois Experts
Home
Profiles
Research units
Research & Scholarship
Datasets
Honors
Press/Media
Activities
Exploiting Inter-Warp Heterogeneity to Improve GPGPU Performance
Rachata Ausavarungnirun
,
Saugata Ghose
, Onur Kayiran
, Gabriel H. Loh
, Chita R. Das
, Mahmut T. Kandemir
, Onur Mutlu
Research output
:
Contribution to journal
›
Conference article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Exploiting Inter-Warp Heterogeneity to Improve GPGPU Performance'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
GPGPU
100%
Caching
100%
Memory Divergence
100%
Divergence Correction
42%
Divergence
28%
Stall
28%
Queuing Delay
28%
Shared Cache
28%
Memory Effect
14%
Impact Performance
14%
GPGPU Computing
14%
Memory-level Parallelism
14%
Management Techniques
14%
High Energy Efficiency
14%
Management Mechanism
14%
Cache Bypassing
14%
Cache Management
14%
Memory Cache
14%
Long Latency
14%
Latency Tolerance
14%
Negative Performance
14%
Hit Rate
14%
Memory Controller
14%
Lockstep
14%
GPU Memory Management
14%
Warp Divergence
14%
Insertion Policy
14%
Heterogeneous Memory
14%
Computer Science
Graphics Processing Unit
100%
Queueing Delay
100%
Energy Efficiency
50%
Performance Impact
50%
Level Parallelism
50%
Memory Controller
50%
Memory Instruction
50%
Hit Rate
50%
Warp Divergence
50%