Title :
APOGEE: adaptive prefetching on GPUs for energy efficiency
Author_Institution :
Dept. of Comput. Sci. & Eng., Chalmers Univ. of Technol., Goteborg, Sweden
Abstract :
Summary form only given. As we have embarked on the multi/many-core roadmap, resource management, especially managing parallelism, is left in the hands of programmers. A major challenge moving forward is how to off-load programmers from the daunting task of managing hardware resources in future parallel architectures to meet higher demands on performance and power efficiency. In this talk I will focus on a number of emerging technologies being developed at Chalmers and elsewhere that can help off-loading programmers from parallelism management. These include task-based dataflow programming models and transactional memory. I will also present a framework for resource management and recent findings concerning how to manage memory hierarchies more power efficiently.
Keywords :
concurrency control; data flow computing; memory architecture; parallel architectures; parallel programming; power aware computing; resource allocation; storage management; automatic resource management; hardware resource management; memory hierarchy management; parallel architecture performance; parallelism management; power efficiency; task-based dataflow programming models; transactional memory; Computer science; Educational institutions; Electronic mail; Parallel architectures; Parallel processing; Resource management; GPU; energy efficiency; prefetching; throughput processing;
Conference_Titel :
Parallel Architectures and Compilation Techniques (PACT), 2013 22nd International Conference on
Conference_Location :
Edinburgh
Print_ISBN :
978-1-4799-1018-2
DOI :
10.1109/PACT.2013.6618798