Embedded memory blocks are important resources in contemporary FPGA devices. When targeting FPGAs, application designers often specify high-level memory functions which exhibit a range of sizes and control structures. These logical memories must be mapped to FPGA embedded memory resources such that physical design objectives are met. In this work a set of power-aware logical-to-physical RAM mapping algorithms are described which convert user-defined memory specifications to on-chip FPGA memory block resources. These algorithms minimize RAM dynamic power by evaluating a range of possible embedded memory block mappings and selecting the most power-efficient choice. Our automated approach has been integrated into a commercial FPGA compiler and tested with 40 large FPGA benchmarks. Through experimentation, we show that, on average, embedded memory dynamic power can be reduced by 21% and overall core dynamic power can be reduced by 7% with a minimal loss (1%) in design performance.
Metastability is a phenomenon that can cause system failures in digital circuits. It may occur whenever signals are being transmitted across asynchronous or unrelated clock domains. The impact of metastability is increasing as process geometries shrink and supply voltages drop faster than transistor Vts. FPGA technologies are significantly affected since leading edge FPGAs are amongst the first devices to adopt the most recent process nodes. In this paper, we present a comprehensive suite of techniques for modeling, characterizing and optimizing metastability effects in FPGAs. We first discuss a theoretical model of metastability, and verify the predictions using both circuit level simulations and board measurements. Next we show how designers have traditionally dealt with metastability problems and contrast that with the automatic CAD algorithms described in this paper that both analyze and optimize metastabilityrelated issues. Through our detailed experimental results, we show that we can improve the metastability characteristics of a large suite of industrial benchmarks by an average of 268,000 times with our optimization techniques.
Accessibility is an important quality attribute for Web applications. The W3C has defined a set of guidelines that must be followed to deploy accessible web applications, however there is no process that support WCAG requirements during the software development lifecycle. This work proposes the inclusion of the WCAG 2.0 accessibility concerns in a Model-Driven Development, more specifically in the WebML process.
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