Download Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs by Sunil P. Khatri, Kanupriya Gulati PDF
By Sunil P. Khatri, Kanupriya Gulati
This ebook bargains with the acceleration of EDA algorithms utilizing systems resembling FPGAs and GPUs. largely utilized CAD algorithms are evaluated and in comparison for strength acceleration on FPGAs and GPUs. insurance comprises dialogue of stipulations lower than which it really is optimum to exploit one platform over one other, e.g., whilst an EDA challenge has a excessive measure of knowledge parallelism, the GPU is sometimes the popular platform, while whilst the matter has extra keep an eye on, an FPGA can be hottest. effects are provided for the acceleration of numerous CAD algorithms (fault simulation, fault desk iteration, version card evaluate in SPICE, Monte Carlo statistical static timing analysis), demonstrating speedups from 30X to 800X. This e-book serves as a worthwhile consultant on how most sensible to leverage parallelism to speed up CAD algorithms. It additionally offers a strategy to extract instantly SIMD parallelism from standard uniprocessor code. With this process, uniprocessor code can instantly be switched over to GPU code, taking into account major acceleration. This procedure is very valuable, given that various GPUs have significantly diverse standards, making the handbook iteration of GPU code an unscalable proposition.
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Extra info for Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs
Further, evolving standards and protocols can be accommodated relatively easily, since design changes are much simpler to incorporate. 6 Scalability 15 can initially be programmed to perform one function such as a self-test and/or board/system test, and it can then be reprogrammed to perform its main task. FPGA vendors provide software and hardware IP cores  that implement several common processing functions. More recently, high-end FPGAs have become available that contain one or more embedded microprocessors.
Com/object/product-tesla-s1070-us. html 14. The Death of the Structured ASIC. php/ articleId/434/issueId/16 15. Valgrind. org/ 16. : An effective power mode transition technique in MTCMOS circuits. In: Proceedings, IEEE Design Automation Conference, pp. 13–17 (2005) 17. : A minimum total power methodology for projecting limits on CMOS GSI. IEEE Transactions Very Large Scale Integration Systems 8(3), 235–251 (2000) 18. : A novel synthesis approach for active leakage power reduction using dynamic supply gating.
From a security point of view, protecting soft IPs is a much more challenging task than protecting hard IPs. Soft IPs are hard to trace and therefore not preferred in highly secure application scenarios. Compared to a CPU/GPU-based implementation, FPGA and custom IC designs are truly hard implementations. Software-based systems like CPUs and GPUs, on the other hand, often involve several layers of abstraction to schedule tasks and share resources among multiple processors or software threads. The driver layer controls hardware resources and the operating system manages memory and processor utilization.