By Li Hu, Weiwei Peng, Yong Hu (auth.), Ford Lumban Gaol, Quang Vinh Nguyen (eds.)

The most recent innovations in computing device expertise effect so much of human day-by-day actions. within the close to destiny, there's tendency that each one of point of human existence could be depending on computing device purposes. In production, robotics and automation became very important for top of the range items. In schooling, the version of educating and studying is focusing extra on digital media than conventional ones. matters on the topic of power reductions and surroundings is turning into serious.

Computational technology may still increase the standard of human existence, not just remedy their difficulties. Computational technology might be useful people to make clever judgements through proposing offerings and their attainable results. Computational technology might help us make feel of observations, comprehend common language, plan and cause with wide historical past wisdom. Intelligence with knowledge may be an final objective for human-oriented science.

This e-book is a compilation of a few contemporary examine findings in machine program and computational technological know-how. This e-book offers state of the art money owed in laptop keep an eye on and Robotics, desktops in schooling and studying applied sciences, desktop Networks and knowledge Communications, info Mining and knowledge Engineering, power and gear structures, clever structures and self reliant brokers, net and internet platforms, medical Computing and Modeling, sign, photograph and Multimedia Processing, and software program Engineering.

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However, power Static Power Optimization for Homogeneous Multiple GPUs 29 consumption is an important issue to computers, so optimizing performance of long running kernels and reducing power consumption are the problems we concerned. We present an energy optimization model considering performance constraint for homogeneous multi-GPUs, and give the performance prediction model when task partitioning policy is specified. We attribute the problem of static power optimization for homogeneous multi-GPUs to the problem of task partitioning problems.

It stores all the counters with a basic array and an overflow array; and when the counter length changes the basic array does not change and overflow array is reconstructed. This structure is a bit similar to our common dynamic structure, but Dynamic Count Filter is designed for the application of multi-set and data flow. [9] also introduces a data structure with the same function with CBF to denote multi-set more effectively in the place of CBF, but it does not provide relevant experiment data to prove its analysis.

If we assign more thread blocks to a SM in a GPU, it will take the SM more time to compute the thread blocks and the pipeline will be used more effectively, meanwhile, the GPU access latency of host memory will be hidden too. In conclusion, the computation time of GPU is glowing slower than the data size of tasks. In other words, Comp(k · e) ≤ k ·Comp(e) (k ≥ 1). Static Power Optimization for Homogeneous Multiple GPUs 23 6000 5500 G EMM 5000 L aplace 4500 cycles 4000 3500 3000 2500 2000 1500 1000 500 2 4 6 8 10 #thread blocks 12 14 16 Fig.

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