Digital signal processing (2nd ed.): principles, algorithms, and applications
Digital signal processing (2nd ed.): principles, algorithms, and applications
Real-time sonar beamforming on high-performance distributed computers
Parallel Computing
PM2: a high performance communication middleware for heterogeneous network environments
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real-Time Systems
SKaMPI: A Detailed, Accurate MPI Benchmark
Proceedings of the 5th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Real-time sonar beamforming on workstations using process networksand POSIX threads
IEEE Transactions on Signal Processing
Enabling on-chip diversity through architectural communication design
Proceedings of the 2004 Asia and South Pacific Design Automation Conference
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
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Recently there has been a lot of interest in improving the infrastructure used in medical applications. In particular, there is renewed interest on non-invasive, high-resolution diagnostic methods. One such method is digital, 3D ultrasound medical imaging. Current state-of-the-art ultrasound systems use specialized hardware for performing advanced processing of input data to improve the quality of the generated images. Such systems are limited in their capabilities by the underlying computing architecture and they tend to be expensive due to the specialized nature of the solutions they employ.Our goal in this work is twofold: (i) To understand the behavior of this class of emerging medical applications in order to provide an efficient parallel implementation and (ii) to introduce a new benchmark for parallel computer architectures from a novel and important class of applications. We address the limitations faced by modern ultrasound systems by investigating how all processing required by advanced beamforming algorithms can be performed on modern clusters of high-end PCs connected with low-latency, high-bandwidth system area networks. We investigate the computational characteristics of a state-of-the-art algorithm and demonstrate that today's commodity architectures are capable of providing almost-real-time performance without compromising image quality significantly.