Name
Title | ||
|---|---|---|
Performance characterization and optimization of mobile augmented reality on handheld platforms |
Abstract | ||
|---|---|---|
The introduction of low power general purpose processors (like the Intelreg Atomtrade processor) expands the capability of handheld and mobile Internet devices (MIDs) to include compelling visual computing applications. One rapidly emerging visual computing usage model is known as mobile augmented reality (MAR). In the MAR usage model, the user is able to point the handheld camera to an object (like a wine bottle) or a set of objects (like an outdoor scene of buildings or monuments) and the device automatically recognizes and displays information regarding the object(s). Achieving this on the handheld requires significant compute processing resulting in a response time in the order of several seconds. In this paper, we analyze a MAR workload and identify the primary hotspot functions that incur a large fraction of the overall response time. We also present a detailed architectural characterization of the hotspot functions in terms of CPI, MPI, etc. We then implement and analyze the benefits of several software optimizations: (a) vectorization, (b) multi-threading, (c) cache conflict avoidance and (d) miscellaneous code optimizations that reduce the number of computations. We show that a 3X performance improvement in execution time can be achieved by implementing these optimizations. Overall, we believe our analysis provides a detailed understanding of the processing for a new domain of visual computing workloads (i.e. MAR) running on low power handheld compute platforms. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IISWC.2009.5306788 | IISWC |
Keywords | Field | DocType |
compelling visual computing application,mar workload,software optimization,execution time,handheld camera,response time,hotspot function architectural characterization,miscellaneous code optimization,cache conflict avoidance,miscellaneous code optimizations,vectorization,mobile augmented reality optimization,handheld platform,multi-threading,low-power electronics,image recognition,performance characterization,augmented reality,displays information recognition,notebook computers,overall response time,low power,mar usage model,performance evaluation,mobile augmented reality,software optimizations,mobile internet device,low power general purpose processor,visual computing application,databases,code optimization,multi threading,pixel,low power electronics,handheld computer,image resolution,optimization | Program optimization,Visual computing,Multithreading,Computer architecture,Cache,Computer science,Mobile Internet device,Parallel computing,Augmented reality,Mobile device,Performance improvement,Embedded system | Conference |
ISBN | Citations | PageRank |
978-1-4244-5157-2 | 10 | 0.86 |
References | Authors | |
7 | 10 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sadagopan Srinivasan | 1 | 120 | 7.87 |
| Zhen Fang | 2 | 91 | 7.62 |
| Ravishankar K. Iyer | 3 | 1119 | 75.72 |
| Steven Zhang | 4 | 22 | 2.63 |
| Mike Espig | 5 | 17 | 2.38 |
| Don Newell | 6 | 512 | 32.67 |
| Daniel Cermak | 7 | 10 | 0.86 |
| Yi Wu | 8 | 48 | 5.75 |
| Igor Kozintsev | 9 | 485 | 55.33 |
| Horst Haussecker | 10 | 596 | 63.76 |