Neha V. Karanjkar

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We propose a new approach to simulation-based design optimization of multi core systems, over a large number of discrete parameters. In this approach, we embed the discrete parameter space into an extended continuous space and apply continuous space optimization techniques over the embedding to search for optimal designs. Such continuous space techniques(More)
Recently a new CMOS current-mode pseudo-exponential function generator circuit was reported by Popa. The entire analysis and exponential function generator circuit, given in Popa’s paper, is based on a current-squaring circuit module. In this comment paper we show that the current-squarer circuit, presented in Popa’s paper, does not work as a current(More)
Modern multi-core systems have a large number of design parameters, most of which are discrete-valued, and this number is likely to keep increasing as chip complexity rises. Further, the accurate evaluation of a potential design choice is computationally expensive because it requires detailed cycleaccurate system simulation. If the discrete parameter space(More)
In simulation-based optimization of queuing systems, the presence of discrete-valued parameters (such as buffer sizes and the number of servers) makes the optimization difficult. We propose a novel technique for embedding such discrete parameters into a continuous space, so that optimization can be performed efficiently using continuous-space methods.(More)
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