Reducing register file size through instruction pre-execution enhanced by value prediction

2009 ◽  
Author(s):  
Yusuke Tanaka ◽  
Hideki Ando
Keyword(s):  
Register File ◽  
File Size ◽  
Value Prediction

Evaluating register file size in ASIP design

2001 ◽  
Author(s):  
Manoj Kumar Jain ◽  
Lars Wehmeyer ◽  
Stefan Steinke ◽  
Peter Marwedel ◽  
M. Balakrishnan
Keyword(s):  
Register File ◽  
File Size

Analysis of the influence of register file size on energy consumption, code size, and execution time

2001 ◽  
Vol 20 (11) ◽  
pp. 1329-1337 ◽  
Author(s):  
L. Wehmeyer ◽  
M.K. Jain ◽  
S. Steinke ◽  
P. Marwedel ◽  
M. Balakrishnan
Keyword(s):  
Energy Consumption ◽  
Execution Time ◽  
Register File ◽  
File Size ◽  
Code Size

scholarly journals Performance Tuning Techniques for Face Detection Algorithms on GPGPU

2020 ◽  
Vol 10 (2) ◽  
pp. 103-108
Author(s):  
Yara M. Abdelaal ◽  
M. Fayez ◽  
Samy Ghoniemy ◽  
Ehab Abozinadah ◽  
H. M. Faheem
Keyword(s):  
Face Detection ◽  
Performance Tuning ◽  
Double Precision ◽  
Occupancy Rate ◽  
Register File ◽  
File Size ◽  
Detection Algorithms ◽  
And Performance ◽  
Gpu Architectures ◽  
Common Face

Face detection algorithms varies in speed and performance on GPUs. Different algorithms can report different speeds on different GPUs that are not governed by linear or nearlinear approximations. This is due to many factors such as register file size, occupancy rate of the GPU, speed of the memory, and speed of double precision processors. This paper studies the most common face detection algorithms LBP and Haar-like and study the bottlenecks associated with deploying both algorithms on different GPU architectures. The study focuses on the bottlenecks and the associated techniques to resolve them based on the different GPUs specifications.

Variable Precision Depth Encoding for 3D Range Geometry Compression

2020 ◽  
Vol 2020 (17) ◽  
pp. 34-1-34-7
Author(s):  
Matthew G. Finley ◽  
Tyler Bell
Keyword(s):  
Normal Distribution ◽  
Arbitrary Distribution ◽  
File Size ◽  
Geometry Compression ◽  
Variable Precision ◽  
Wide Range ◽  
Novel Method ◽  
Encoding Method ◽  
Rgb Image ◽  
Color Channels

This paper presents a novel method for accurately encoding 3D range geometry within the color channels of a 2D RGB image that allows the encoding frequency—and therefore the encoding precision—to be uniquely determined for each coordinate. The proposed method can thus be used to balance between encoding precision and file size by encoding geometry along a normal distribution; encoding more precisely where the density of data is high and less precisely where the density is low. Alternative distributions may be followed to produce encodings optimized for specific applications. In general, the nature of the proposed encoding method is such that the precision of each point can be freely controlled or derived from an arbitrary distribution, ideally enabling this method for use within a wide range of applications.

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