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Piero Belforte

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This document should be very interesting to an engineer because it reports a not biased experimental validation of a predictive tool carried out by a customer for an actual multiboard avionics design. The general considerations are reported at the beginning of the document...the conclusion is that a tool like PRESTO can save up to a 30% in the development time of a system like this . I have other papers reporting validations but these refers to specific non production test vehicules. Then if you give a quick look to the rest of the doc you will have an idea of what is the level of compliance between measurements and predictions...some results are very close together and other shows differences up to 70% or so...but we as engineers we have always to consider the min-max spread of technical specs for digital components may be in order of 100% or more of typical value so it is a nonsense trying to achieve better compliance. Moreover the digital test patterns involved are not the actual ones , and this can make a significant difference, even if Presto was provided with a feature allowing the user to put in the model actual test patterns as input stimuli. Presto was a state-of-the art post -layout tool at this time and this thanks to both the simulation engine (SPRINT, the predecessor of DWS) and to the modeling techniques including PD planes. Extracted nets of up to hundreds of thousands of lines (circuital elements) were simulated in some tens of minutes on machines that were 1000 times slower than today PCs. A true CO-SIMULATION of SI , PI and EMC was performed...no other commercial tool was able to achieve this performance level. This can give you an idea of the capabilties of both DWS and related modeling methods like BTM ...the PI/SI examples I'm building up for Spicy SWAN are only a very small subset of the complexity Presto was able to deal with.

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Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

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Thris Flyer 1996

1. Piero Belforte THRIS flyer 1996 1

2. Piero Belforte THRIS flyer 1996 2

3. Piero Belforte THRIS flyer 1996 3

4. Piero Belforte THRIS flyer 1996 4

5. Piero Belforte THRIS flyer 1996 5

6. Piero Belforte THRIS flyer 1996 6

Thris Flyer 1996

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Thris Flyer 1996