| dc.description.abstract | Changing environment in the current technologies have introduce a gap between the
ever growing needs of users and the state of present designs. As high data and hard
computation applications moved forward in the near future, the current trend reaches
for a greater performance. Approximate computing enters this scheme to boost a system
overall attributes, while working with intrinsic and error tolerable characteristics both in
software and hardware. This work proposes a multicore and multi-accelerator platform
design that uses both exact and approximate versions, also providing interaction with a
software counterpart to ensure usage of both layouts. A set of five di↵erent approximate
accelerator versions and one exact, are present for three di↵erent image processing filters,
Laplace, Sobel and Gauss, along with their respective characterization in terms of Power,
Area and Delay time. This will show better results for design versions 2 and 3. Later
it will be seen three di↵erent interfaces designs for accelerators along with a softcore
processor, Altera’s NIOS II. Results gathered demonstrate a definitively improvement
while using approximate accelerators in comparison with software and exact accelerator
implementations. Memory accessing and filter operations times, for two di↵erent matrices
sizes, present a gain of 500, 2000 and 1500 cycles measure for Laplace, Gauss and Sobel
filters respectively, while contrasting software times, and a range of 28-84, 20-40 and
68-100 ticks decrease against the use of an exact accelerator. | |
