We present the system-level design of two accelerators for two microwave imaging algorithms for breast cancer detection. The accelerators were designed in SystemC and optimized via High-Level Synthesis (HLS). The two algorithms stress the capabilities of commercial HLS tools in different ways: the first is communication-bound and requires careful pipelining of communication and computation; the second is computation-bound and requires the implementation of mathematical functions that are not properly supported by HLS tools. Still, in the span of four months we were able to design and validate about one hundred alternative implementations, targeting a Zynq SoC platform. Furthermore, we were pleased to obtain results that are superior to a previous RTL implementation, which confirms the remarkable progress of HLS tools.

Acceleration of Microwave Imaging Algorithms for Breast Cancer Detection via High-Level Synthesis / Jahier Pagliari, Daniele; Casu, Mario Roberto; Carloni, Luca P.. - ELETTRONICO. - (2015), pp. 475-478. ((Intervento presentato al convegno 33rd IEEE International Conference on Computer Design (ICCD) tenutosi a New York City (USA) nel 18-21 Ottobre 2015 [10.1109/ICCD.2015.7357152].

Acceleration of Microwave Imaging Algorithms for Breast Cancer Detection via High-Level Synthesis

JAHIER PAGLIARI, DANIELE;CASU, MARIO ROBERTO;
2015

Abstract

We present the system-level design of two accelerators for two microwave imaging algorithms for breast cancer detection. The accelerators were designed in SystemC and optimized via High-Level Synthesis (HLS). The two algorithms stress the capabilities of commercial HLS tools in different ways: the first is communication-bound and requires careful pipelining of communication and computation; the second is computation-bound and requires the implementation of mathematical functions that are not properly supported by HLS tools. Still, in the span of four months we were able to design and validate about one hundred alternative implementations, targeting a Zynq SoC platform. Furthermore, we were pleased to obtain results that are superior to a previous RTL implementation, which confirms the remarkable progress of HLS tools.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2616937