IEEE Signal Processing Society, Santa Clara Valley Chapter

Workshop on FPGAs for Digital Signal Processing Applications

 

Location: Bannan Engineering Laboratories, School of Engineering, Santa Clara University

Date: Saturday, Feb. 7, 2009

Time: 8:00am – 5:00pm

 

 

Workshop Program

 

 

1. Why and when to use DSPs, FPGAs and ASICs

Speaker: Dr. Xiaoshu Qian, Intel Corporation

 

Abstract:

We will provide a brief up-to-date comparison of Digital Signal Processors (DSPs), Field-Programmable Gate Arrays (FPGAs), and Application Specific ICs (ASICs) to set the stage for subsequent presentations on using FPGAs for digital signal processing. We will compare these technologies in terms of the programmability, speed, power consumptions and cost, and highlight the major progresses in the last few years. 

 

 

 

 

2. FPGA Architectures for H.264 Video Processing

Speaker: Prof. Tokunbo Ogunfunmi, Director, Signal Processing Research Lab. (SPRL), Dept. of Electrical Engineering,Santa Clara University

http://www.scu.edu/engineering/ee/people/ogunfunmi.cfm

 

Abstract:

H.264/AVC is a very important standard in video compression/transmission area because of its high coding efficiency and robustness. H.264 is an ITU video standard used in many scalable video applications. In this talk, we review the basics of H.264 and more recent standards, then we cover hardware architectures for processing major parts of the standard. These include motion estimation, and transform and quantization.  We focus on architectures that are configurable and implementable on FPGAs such as the Xilinx FPGA. We present two examples:  A new hardware architecture for 8x8 integer transform and quantization for H.264 which promises minimal resource utilization. In the architecture, each pixel is processed one by one on a simplified pipeline without multiplication. Thus, redundant modules, which are used for block-based or row-based parallel processing, can be reduced.  Experimental results show that it can reduce resource 30% compared to previously proposed models. It covers wide ranges of parameters as well.  A hybrid fast motion estimation algorithm – Simplified  Unified Mult-Hexagon (SUMH) search (also known as the Simplified Fast Motion Estimation (SFME) algorithm), is a non-normative part of the H.264/AVC standard. We have made hardware-oriented modifications to SUMH and implemented a configurable, pipelined hardware architecture for the modified SUMH. The architecture is prototyped using Digilent XUP V2P board which contains a Virtex-II Pro XC2VP30 Xilinx FPGA and is capable of  processing CIF frame sequences in real-time.

 

 

 

 

3. FPGAs: Re-Inventing the Signal Processor and MIMO-OFDM Applications

Speaker: Dr. Chris Dick, Xilinx Inc.

 

Abstract:

As semiconductors become more complex and new milestones in transistor size and performance are achieved, power consumption and thermal management have emerged as limiting factors to the continued pace of chip design and manufacturing of high-performance devices. Moving to the era of multi-billion transistor chips, device technology evolution along the same axis is not sustainable, because we would be looking to build devices that run as hot as a rocket engine exhaust nozzle. The solution is commercial deployment of concurrent processing.

 

While parallel processing for DSP has roots going back several decades, its promise of high-performance has not really been delivered until recently. The delivery vehicle is the field programmable gate array (FPGA). While early attempts to commercialize parallel DSP failed, the technology context is now right for providing high-performance signal processing platforms based on concurrent computing concepts. The presentation provides an overview of FPGA signal processing and contrasts the FPGA DSP with other technologies that are employed for solving real-time signal processing problems.

 

MIMO-OFDM is a cornerstone technology for many key wireless communication systems and many of the key signal processing tasks performed in these systems require significant arithmetic resourcing. Further, it is often desirable to maintain an element of flexibility in these systems in order to extend network functionality with new signal processing capabilities once the system is deployed, or to allow the one hardware platform to support multiple air interfaces. The joint requirement of flexibility and high-performance is one of the reasons that make this application space well suited to realization using FPGAs. This presentation will provide an overview of the architecture and FPGA implementation of a MIMO-OFDM communication system using a Simulink® -based tool chain called System Generator for DSP. Moving forward, one of the key requirements of virtually all wireless systems will be increased data capacity. For OFDM modulation, one of the natural methods for delivering increased data rates is spatial multiplexing (SM) MIMO. There are significant computational challenges to the realization of maximum likelihood (ML), or quasi-ML, SM MIMO decoders. The presentation provides an overview of the FPGA realization of a sphere detector for SM MIMO waveforms. The architecture and micro-architecture design considerations for producing  efficient FPGA implementations of these decoders are examined.

 

 

 

 

4. FPGA-Based Embedded Wideband Audio Codec System

Speaker: Prof. Chang Choo, College of Engineering, San Jose State University

http://www.engr.sjsu.edu/choo/

 

Abstract:

G.729.1 is an 8-32 kbps scalable wideband speech and audio codec interoperable with G.729, G.729A and G.729B. It, however, requires much more computation than its narrowband coders. In this talk, hardware IPs for accelerating the peformance of the G.729.1 will be presented. The IPs are implemented on an embedded FPGA platform, where a soft processor works with them, resulting in a significant performance improvement.

 

 

 

 

5. A Platform-Based Approach to Realizing High Performance DSP Subsystems in FPGAs

Speaker: Dr. Jim Hwang, Xilinx Inc.

 

Abstract:

FPGAs have become key components in implementing high performance DSP systems, especially in the areas of digital communications, video, and image processing.  The compute/memory bandwidth of a modern FPGA far exceeds that of a microprocessor or DSP processor running at clock rates two to ten times that of the FPGA, and with their capability for realizing highly parallel arithmetic micro-architectures, FPGAs are ideally suited for creating custom data path processors.  Despite these characteristics, FPGAs have not been broadly adopted in the DSP community because traditional programming models are based around hardware description languages (HDLs) like VHDL and Verilog, and electronic design automation tools that are foreign to most signal processing engineers.

 

In the recent years, a number of commercial design tools have made strides in bridging the gap between the C programming language and HDLs, and between the MATLAB / Simulink environment (The Mathworks, Inc.) and HDLs and hardware-centric intellectual property (IP) libraries especially targeting FPGAs.  This presentation describes a platform-based approach to realizing DSP systems in FPGAs that combines algorithm-centric programming models, high-level modeling environments, automatic code generation, standard hardware platforms, and embedded software.  We demonstrate ways in which the platform provides descriptive expressiveness, fine-grained control of hardware architecture, and faithful simulation semantics from a system level environment.  With interfaces and abstractions to implement data paths, control, and embedded software, each in a language suited to a particular function, and with heterogeneous simulation semantics and deployment, this platform enables a DSP design team to target FPGAs with less FPGA-specific expertise than ever before possible. 

 

 

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