Abstract:
Data movement between the compute and the storage (e.g., GPU and SSD) has been a long-neglected problem in heterogeneous systems, while the inefficiency in existing syste...Show MoreMetadata
Abstract:
Data movement between the compute and the storage (e.g., GPU and SSD) has been a long-neglected problem in heterogeneous systems, while the inefficiency in existing systems does cause significant loss in both performance and energy efficiency. This paper presents Hippogriff to provide a high-level programming model to simplify data movement between the compute and the storage, and to dynamically schedule data transfers based on system load. By eliminating unnecessary data movement, Hippogriff can speedup single program workloads by 1.17×, and save 17% energy. For multi-program workloads, Hippogriff shows 1.25× speedup. Hippogriff also improves the performance of a GPU-based MapReduce framework by 27%.
Date of Conference: 02-05 October 2016
Date Added to IEEE Xplore: 24 November 2016
ISBN Information: