Multicore CPUs 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) on embedded platforms are different from their desktop counterparts due to their memory and computational limitations. This book evaluates the performance and energy efficiency achieved by offloading Java applications to an embedded GPU. 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.
Accelerating Java on Embedded GPU (Paperback)
info:
We aim to show you accurate product information. Manufacturers, suppliers and others provide what you see here, and we have not verified it. Â
Specifications
Book format
Paperback
Fiction/nonfiction
Non-Fiction
Publication date
May, 2014
Pages
128
Warranty
Warranty information
Please be aware that the warranty terms on items offered for sale by third party Marketplace sellers may differ from those displayed in this section (if any). To confirm warranty terms on an item offered for sale by a third party Marketplace seller, please use the 'Contact seller' feature on the third party Marketplace seller's information page and request the item's warranty terms prior to purchase.