The Maryland DSPCAD Research Group


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The DSPCAD Group is affiliated with the Department of Electrical and Computer Engineering, and Institute for Advanced Computer Studies, and is directed by Prof. Shuvra S. Bhattacharyya. Research in the DSPCAD Group focuses on computer-aided design (CAD) and implementation of digital signal processing (DSP) systems. DSP refers to the digital analysis and manipulation of data streams, such as those associated with audio signals, biomedical signals, control system components, digital communications waveforms, images, video streams. We work on many aspects of architectures, models of computation, and software tools for DSP system design, including specialized programming languages; synthesis and optimization of hardware and software; hardware/software co-design; and DSP implementations on field-programmable gate arrays (FPGAs), multicore processors, graphics processing units (GPUs), and application-specific integrated circuits (ASICs). The long-term goal of this research is to improve the productivity of designing DSP systems, as well as the efficiency, reliability, and security of DSP system implementations. Active research projects in the group, and areas in which we have made significant accomplishments include the following topics:


bullet The dataflow interchange format (DIF), a dataflow language for design and implementation of signal processing systems.
bullet DICE: The DSPCAD Integrative Command Line Environment.
bullet LIDE: The DSPCAD Lightweight Dataflow Environment.
bullet GPU-based acceleration of signal processing applications.
bullet Memory and buffer management for DSP hardware and software.
bullet Applications and tools for configurable computing.
bullet Mapping algorithms onto multiprocessor DSP systems.
bullet New computational models for more efficient programming of DSP systems.
bullet Novel architectures for improving performance and predictability of DSP applications.
bullet Low power implementation of embedded applications.
bullet Architecture and optimizations for low power sensor networks.

For more information go to the DSPCAD Projects Page.