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Karl Fergusen
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re: Opinion: Using GPUs to accelerate EDA applications
Karl Fergusen   5/3/2012 7:05:05 PM
We started using Jacket a few months ago to accelerate MatLab codes at L-3 on the GPU. Awesome speedups!

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re: Opinion: Using GPUs to accelerate EDA applications
Les_Slater   5/6/2012 1:20:21 AM
The problem of rethinking algorithmic foundations is an interesting one. This needs to be taken on as a general formality of a geometry of problem space.

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re: Opinion: Using GPUs to accelerate EDA applications
TingLu   5/7/2012 4:17:38 AM
Simulation acceleration has been dominant by FPGA. I am wondering how well it is compared with GPU.

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re: Opinion: Using GPUs to accelerate EDA applications
urital.rocketick   5/7/2012 5:31:01 AM
Hi TingLu, FPGA-based accelerators enable to run chip designs at MHz speeds and to debug system-level scenarios in the lab, but they are not simulators. It is just a different product category. Pros: - You can reach 1-10MHz speeds with them and therefore debug your driver and even your application in embedded systems Cons: - They are very expensive. - Require significant ramp-up time, and then if you change your code or libraries you are not really debugging your real silicon design - Does not work alongside your existing test-bench (verification environment), and if it does you cannot reach MHz speeds. - Limited in capacity (to scale you need to add more FPGAs/boxes but then you trade-off with speed) - Lack support for non-synthesize-able code - No support for 4-state logic - Lack full visibility - Long compilation time (require to synthesys and place-and-route)

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re: Opinion: Using GPUs to accelerate EDA applications
docdivakar   5/11/2012 6:09:10 AM
Existing (not optimally parallel) EDA tools can still exploit the operating system to benefit from parallelism. Examples abound, like the pattern-based DRC; in the TCAD area, computational lithography, etc. MP Divakar

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