Abstract | ||
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Usage models and applications are rapidly changing as a new class of devices (smart phones, smart TVs, etc) and rich cloud computing services (on datacenter servers) enter the marketplace. In this talk, I will start by describing some key examples of these radical changes in usage models, applications and devices. I will then highlight why the next decade of computing (clients and servers) will be based on heterogeneous architectures consisting of asymmetric cores, accelerators and hybrid cache/memory structures. The rest of the talk will be an in-depth discussion of the power/performance analysis challenges for heterogeneous architectures, such as (i) how do we analyze applications to determine the right mix of cores and accelerators, (ii) how do we provide performance/power prediction techniques for efficient OS scheduling on heterogeneous architectures?, (iii) how do we enable runtimes and applications to achieve the required QoS on heterogeneous architectures?, (iv) how do simulation/emulation methodologies and infrastructure have to change for rapid and consistent heterogeneous architecture exploration? For each of these, I will also give examples of work that is on-going and outline potential areas for future work on performance/power analysis for heterogeneous architectures. |
Year | DOI | Venue |
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2011 | 10.1109/ISPASS.2011.5762709 | Performance Analysis of Systems and Software |
Keywords | Field | DocType |
smart tvs,future work,power analysis,heterogeneous architecture,performance analysis challenge,rich cloud computing service,power prediction technique,consistent heterogeneous architecture exploration,smart phone,usage model,software architecture,cloud computing | Power analysis,Computer architecture,Cache,Scheduling (computing),Computer science,Parallel computing,Server,Quality of service,Real-time computing,Emulation,Software architecture,Cloud computing | Conference |
ISBN | Citations | PageRank |
978-1-61284-367-4 | 0 | 0.34 |
References | Authors | |
0 | 1 |
Name | Order | Citations | PageRank |
---|---|---|---|
Ravishankar Iyer | 1 | 720 | 35.52 |