Paper Info
Title
Speculative execution on multi-GPU systems
Abstract
Abstract—The lag of parallel programming,models,and,lan- guages,behind,the advance,of heterogeneous,many-core,pro- cessors has,left a gap,between,the computational,capability of modern,systems,and,the ability of applications,to exploit them. Emerging programming models, such as CUDA and OpenCL, force developers to explicitly partition applications into components,(kernels) and,assign them,to accelerators in order to utilize them,effectively. An accelerator is a processor,with a different ISA and,micro-architecture than the main,CPU. These static partitioning schemes,are effective when,targeting a system with only a single accelerator. However, they are not robust to changes,in the number,of accelerators,or the performance characteristics of future generations,of accelerators. In previous work, we presented the Harmony execution model for computing,on,heterogeneous,systems,with,several CPUs and accelerators. In this paper, we extend Harmony to target systems,with,multiple,accelerators,using,control,speculation to expose,parallelism. We,refer to this technique,as Kernel Level Speculation (KLS). We argue that dynamic,parallelization techniques such as KLS are sufficient to scale applications across several accelerators based on the intuition that there will be fewer distinct accelerators than,cores within each,accelerator. In this paper, we use a complete prototype of the Harmony runtime that we developed,to explore the design decisions and trade-offs in the implementation,of KLS. We show,that KLS improves,parallelism to a sufficient degree,while retaining a sequential programming model. We accomplish,this by demonstrating,good scaling of KLS on a highly heterogeneous,system,with three distinct accelerator types and,ten processors.
Year
DOI
Venue
2010
10.1109/IPDPS.2010.5470427
Parallel & Distributed Processing
Keywords
DocType
ISSN
coprocessors,multiprocessing systems,parallel programming,cuda,harmony execution model,harmony runtime,isa,opencl,accelerator,application partitioning,components,computational capability,dynamic parallelization techniques,heterogeneous many-core processors,heterogeneous system,kernel level speculation,micro-architecture,multi-gpu systems,parallel programming languages,parallel programming models,sequential programming model,speculative execution,parallel programming model,programming model
Conference
1530-2075
ISBN
Citations 
PageRank 
978-1-4244-6442-5
11
0.60
References 
Authors
17
2
Name
Order
Citations
PageRank
Gregory Frederick Diamos1111751.07
Sudhakar Yalamanchili21836184.95