Download Advances in Computer Systems Architecture: 11th Asia-Pacific by Guang R. Gao (auth.), Chris Jesshope, Colin Egan (eds.) PDF

By Guang R. Gao (auth.), Chris Jesshope, Colin Egan (eds.)

On behalf of all the humans fascinated by this system choice, this system committee participants in addition to a variety of different reviewers, we're either relieved and happy to offer you with the court cases of the 2006 Asia-Pacific desktops structure convention (ACSAC 2006), that is being hosted in Shanghai on September 6–8, 2006. this can be the eleventh in a sequence of meetings, which all started lifestyles in Australia, because the machine structure component to the Australian desktop technological know-how Week. In 1999 it ventured clear of its roots for the 1st time, and the fourth Australasian laptop structure convention used to be held within the appealing urban of Sails (Auckland, New Zealand). might be it was once due to a scarcity of the other computing device structure convention in Asia or simply the charm of touring to the Southern Hemisphere however the convention grew to become more and more foreign in the course of the next 3 years and in addition replaced its identify to incorporate computers structure, reflecting extra the scope of the convention, which embraces either architectural and platforms concerns. In 2003, the convention back ventured offshore to mirror its constituency and because then has been held in Japan within the appealing urban of Aizu-Wakamatsu, through Beijing and Singapore. This yr it back returns to China and subsequent 12 months will circulation to Korea for the 1st time, the place it will likely be prepared by means of the Korea University.

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Extra resources for Advances in Computer Systems Architecture: 11th Asia-Pacific Conference, ACSAC 2006, Shanghai, China, September 6-8, 2006. Proceedings

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The following equality, which follows immediately from (6), will be useful in the sequel 1−α= −eL U + eU L . eL − eU (8) Observe that the relative error is now ε(x) = e x − c1 − c2 x , ex x ∈ I. (9) Comparying ε(L) and ε(U ) gives e U − c1 − c2 U e L − c1 − c2 L = . eU eL Hence, using (6), c2 = c1 e L − e U c1 = . −eL U + eU L 1−α (10) Implementations of Square-Root and Exponential Functions 19 Substituting for c2 into (9) we obtain c1 x ex − c1 − 1−α , x e and differentiation with respect to x yields ε(x) = ε (x) = c1 e−x 1 − x ∈ I, (11) x−α 1 (1 − x) = c1 e−x , 1−α 1−α x ∈ I.

Scientific computing applications contain a great lot of loops possessing a high degree of instruction, data and task level parallelism that can be exploited by decomposing the scientific computing task into smaller subtasks, which are mapped into different computational elements, distributing the scientific stream to different processors. However, because a stream program is more complex than an equivalent sequential program, to realize this increase in speed some challenges must be overcome first [12].

Of Int. Symp. on Low Power Electronics and Design, 2003, pp. 593-601. 6. S. Kaxiras, Z. Hu, and M. Martonosi. Cache decay: Exploiting generational behavior to reduce cache leakage power. Proc. of Int. Symp. on Computer Architecture, 2001, pp 240-251. 7. R. Kessler. The Alpha 21264 Microprocessor. IEEE Micro Magazine. 24-36. 8. N. S. Kim, K Flautner, D. Blaauw, and T. Mudge. Circuit and Microarchitectural Techniques for Reducing Cache Leakage Power. 12, no. 2, Feb. 2004, pp 167-184. 9. N. S. Kim, K.

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