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Measuring and tuning energy efficiency on large scale high performance computing platforms

Laros, James H.

Recognition of the importance of power in the field of High Performance Computing, whether it be as an obstacle, expense or design consideration, has never been greater and more pervasive. While research has been conducted on many related aspects, there is a stark absence of work focused on large scale High Performance Computing. Part of the reason is the lack of measurement capability currently available on small or large platforms. Typically, research is conducted using coarse methods of measurement such as inserting a power meter between the power source and the platform, or fine grained measurements using custom instrumented boards (with obvious limitations in scale). To collect the measurements necessary to analyze real scientific computing applications at large scale, an in-situ measurement capability must exist on a large scale capability class platform. In response to this challenge, we exploit the unique power measurement capabilities of the Cray XT architecture to gain an understanding of power use and the effects of tuning. We apply these capabilities at the operating system level by deterministically halting cores when idle. At the application level, we gain an understanding of the power requirements of a range of important DOE/NNSA production scientific computing applications running at large scale (thousands of nodes), while simultaneously collecting current and voltage measurements on the hosting nodes. We examine the effects of both CPU and network bandwidth tuning and demonstrate energy savings opportunities of up to 39% with little or no impact on run-time performance. Capturing scale effects in our experimental results was key. Our results provide strong evidence that next generation large-scale platforms should not only approach CPU frequency scaling differently, but could also benefit from the capability to tune other platform components, such as the network, to achieve energy efficient performance.

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Microkinetic Modeling of Lean NOx Trap Sulfation and Desulfation

Larson, Richard S.

A microkinetic reaction sub-mechanism designed to account for the sulfation and desulfation of a commercial lean NOx trap (LNT) is presented. This set of reactions is appended to a previously developed mechanism for the normal storage and regeneration processes in an LNT in order to provide a comprehensive modeling tool. The reactions describing the storage, release, and reduction of sulfur oxides are patterned after those involving NOx, but the number of reactions is kept to the minimum necessary to give an adequate simulation of the experimental observations. Values for the kinetic constants are estimated by fitting semi-quantitatively the somewhat limited experimental data, using a transient plug flow reactor code to model the processes occurring in a single monolith channel. Rigorous thermodynamic constraints are imposed in order to ensure that the overall mechanism is consistent both internally and with the known properties of all gas-phase species. The final mechanism is shown to be capable of reproducing the principal aspects of sulfation/desulfation behavior, most notably (a) the essentially complete trapping of SO2 during normal cycling; (b) the preferential sulfation of NOx storage sites over oxygen storage sites and the consequent plug-like and diffuse sulfation profiles; (c) the degradation of NOx storage and reduction (NSR) capability with increasing sulfation level; and (d) the mix of H2S and SO2 evolved during desulfation by temperature-programmed reduction.

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Results 67601–67700 of 99,299
Results 67601–67700 of 99,299