Benchmarking architecture

Benchmarking is widely employed as a methodology to learn about best practice techniques from one s competitors. There are usually around ten generic categories for designing benchmarking architecture ... 

After the description of chemical structure and control of meso-architecture and surface area, selected applications of such carbon materials as battery electrodes, supercapacitors, and in the design of controlled hybrid heterojunctions were presented. In the Li battery, coating or hybridization with hydrothermal carbon brought excellent capacities at simultaneous excellent stabilities and rate performances. This was exemplified by hybridization with Si, Sn02 (both anode materials) as well as LiFeP04 (a cathode material). In the design of supercapacitors, porous HTC carbons could easily reach the benchmark of optimized activated traditional carbons, with better stability and rate performance. 

The widespread adoption by the simulation community of a specific benchmark problem to gauge both the effectiveness and scalability of emerging algorithms, and the suitability of different machine architectures, is to be applauded. 

K. Dowd, High Performance Computing RISC Architectures, Optimization, and Benchmarks, O Reilly and Associates, Sebastopol, CA, 1993. 

The artificial neural network (ANN) based prediction model utilized in the present study is the multilayer perceptrons (MLPs). It is adopted as the benchmark to compare with the time-varying statistical models since it has been shown that the MLP architecture could approximate... 

As the technology improves, new processor architectures arise. The literature in fault tolerance techniques for processor systems usuaUy tests their proposed techniques with sets of benchmarks. We intend to expand our case-study applications to a wider range, including real time and more applications, such as operating systems. 

The benchmark case is of greater stand-alone interest when the network exhibits complexities such as stochastic demand that is filtered through the inventory policies implemented at the successive echelons, intricate cost structures, lead times, and multiple time periods of activity. This is the theme of the bulk of multi-echelon inventory theory, dating back to the serial supply chain analysis of Clark and Scarf (1960). This literature also considers system architectures that move product from a manufacturer to end customers along, multiple parallel paths, such as a 1-depot N-warehouse network. 

A large number of web sites are built using PHP and MySQL on Linux platforms with Apache as the web server. This combination is known as the LAMP architecture. Apache, PHP and MySQL are also available on Windows platforms giving rise to combinations like WAMP (Windows, Ap>ache, MySQL and PHP) and WIMP (where the IIS web server is used instead of Apache). Even though LAMP is a very popular architecture there has been little work to characterize and benchmark the architecture, especially at an application level. 

The KcsA channel is characterized by this simple transmembrane architecture (see Ref. 40, and the left side of Fig. 2), and its activation has been attributed to pH-dependent translations and rotations of the two transmembrane helices.Because of its relative simplicity, KcsA has been simulated extensively with a variety of approaches, and, like gA, it too can be considered a benchmark system for simulation codes. 

Due to the considerable differences in reactant chemistries and testing conditions between the cells presented in Table 6.1, it is difficult to draw final conclusions about which specific device architecture may be optimal. Factors such as reactant species, reactant and electrolyte concentration, flow rate, temperature, separators, patterned electrodes, and the presence of catalysts can all significantly affect the power output of a device. Power density comparisons would ideally be made with devices benchmarked at standardized conditions for example, a liquid/liquid cell could be benchmarked at room temperature with standardized vanadium electrolytes (e.g., 1 M vanadium in 1 M sulfuric acid) and widely available porous carbon electrodes (e.g., Toray carbon paper). Conducting polarization curve and impedance measurements at a range of flow rates would enable full characterization of fuel utilization, mass transport, and ohmic losses which are inherent to the cell structure, and the peak volumetric power density measurements would then enable a direct comparison with other devices. 

We implemented a tool set for the outlined fault-space pruning approach in the Fail [12] FI experimentation framework, configured to run with the Bochs x86 simulator [24]. Ideally, we would simulate faults in a detailed register transfer and gate-level processor model however, since simulation of realistic benchmarks on low-level models is extremely slow, this work chooses a fast architecture simulator. We extended the tracing plugin of Fail with the capability to record the additional machine state listed in Tab. 1 alongside the usual instruction and memory-access trace. 

In general, the ability of a computer system to detect and recover from hardware errors depends on both the hardware architecture and the machine code of the executed software. Hence, when we conduct out-of-context fault injection experiments to assess a software component s ability to handle hardware errors, we must run the experiments on a hardware platform that is similar to the one used in the real product. However, to generalize the benchmarking outcome, different hardware platforms should be considered. 

Such benchmarking experiments aim to measure the likelihood that the executable code of a software component exhibit silent data corruptions (SDCs) for hardware errors that propagate to instruction set architecture (ISA) registers and main memory locations. The purpose of such measurements is to identify weaknesses in the executable code, and thereby finding ways of hardening the code against hardware errors by means of software-implemented hardware fault tolerance techniques. 

There are many technological rules (failure mode and protection mode hypothesis), but although normative, these railway environment rules ate not applied equally between the north and south of Europe or even across the Atlantic". Consequently, an architecture whose safety level is accepted in Germany, will not necessarily be accepted in France, and a product developed according to safety rules for the French market will require one or more modifications to meet North American standards. 1 can assure you there is also inconsistency in the opposite direction. Cross-acceptance by the authorities of technological benchmarks specific to each country is pitted against safety culture dogma. 

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