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Dynamically Reconfigurable Active Cache Modeling


Dynamically Reconfigurable Active Cache Modeling

Barzegar, Ali (2014) Dynamically Reconfigurable Active Cache Modeling. Masters thesis, Concordia University.

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This thesis presents a novel dynamically reconfigurable active L1 instruction and data cache model, called DRAC. Employing cache, particularly L1, can speed up memory accesses, reduce the effects of memory bottleneck and consequently improve the system performance; however, efficient design of a cache for embedded systems requires fast and early performance modeling. Our proposed model is cycle accurate instruction and data cache emulator that is designed as an on-chip hardware peripheral on FPGA. The model can also be integrated into multicore emulation system and emulate multiple caches of the cores. DRAC model is implemented on Xilinx Virtex 5 FPGA and validated using several benchmarks. Our experimental results show the model can accurately estimate the execution time of a program both as a standalone and multicore cache emulator. We have observed 2.78% average error and 5.06% worst case error when DRAC is used as a standalone cache model in a single core design. We also observed 100% relative accuracy in design space exploration and less than 13% absolute worst case timing estimation error when DRAC is used as multicore cache emulator.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Barzegar, Ali
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:14 January 2014
Thesis Supervisor(s):Abdi, Samar
ID Code:978188
Deposited By: ALI BARZEGAR
Deposited On:16 Jun 2014 18:50
Last Modified:18 Jan 2018 17:46
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