Paper out of Oregon State that looks to have just been released:
"SURVEY OF ACCELERATING APPLICATIONS ON MOBILE DEVICE BY GPU PARALLEL
PROGRAMMING"
http://web.engr.oregonstate.edu/~sunr/ece570_project/Fin_report.pdf
--
Regards,
Tom
"Where's the kaboom!? There was supposed to be an earth-shattering
kaboom!" Marvin Martian
Tech Lead, Graphics Working Group | Linaro.org │ Open source software
for ARM SoCs
w) tom.gall att linaro.org
h) tom_gall att mac.com
http://hgpu.org/?p=11648
"
Accelerating Java on Embedded GPU
Iype P. Joseph
Ottawa-Carleton Institute of Electrical and Computer Engineering,
University of Ottawa, Ottawa, Canada
University of Ottawa, 2014
Multicore CPUs (Central Processing Units) and GPUs (Graphics
Processing Units) are omnipresent in today’s market-leading
smartphones and tablets. With CPUs and GPUs getting more complex,
maximizing hardware utilization is becoming problematic. The
challenges faced in GPGPU (General Purpose computing using GPU)
computing on embedded platforms are different from their desktop
counterparts due to their memory and computational limitations. This
thesis evaluates the performance and energy efficiency achieved by
offloading Java applications to an embedded GPU. The existing
solutions in literature address various techniques and benefits of
offloading Java on desktop or server grade GPUs and not on embedded
GPUs. Our research is focussed on providing a framework for
accelerating Java programs on embedded GPUs. Our experiments were
conducted on a Freescale i.MX6Q SabreLite board which encompasses a
quad-core ARM Cortex A9 CPU and a Vivante GC 2000 GPU that supports
the OpenCL 1.1 Embedded Profile. We successfully accelerated Java code
and reduced energy consumption by employing two approaches, namely
JNI-OpenCL, and JOCL, which is a popular Java-binding for OpenCL.
These approaches can be easily implemented on other platforms by
embedded Java programmers to exploit the computational power of GPUs.
Our results show up to an 8 times increase in performance efficiency
and 3 times decrease in energy consumption compared to the embedded
CPU-only execution of Java program. To the best of our knowledge, this
is the first work done on accelerating Java on an embedded GPU.
"
--
Regards,
Tom
"Where's the kaboom!? There was supposed to be an earth-shattering
kaboom!" Marvin Martian
Tech Lead, Graphics Working Group | Linaro.org │ Open source software
for ARM SoCs
w) tom.gall att linaro.org
h) tom_gall att mac.com
