Acceleration of GPU-Based Ultrasound Simulation via Data Compression

Abstract

Abstract-The realistic simulation of ultrasound wave propagation is computationally intensive. The large size of the grid and low degree of reuse of data means that it places a great demand on memory bandwidth. Graphics Processing Units (GPUs) have attracted attention for performing scientific calculations due to their potential for efficiently performing large numbers of floating point computations. However, many applications may be limited by memory bandwidth, especially for data sets whose size is larger than that of the GPU platform. This problem is only partially mitigated by applying the standard technique of breaking the grid into regions and overlapping the computation of one region with the host-device memory transfer of another.In this paper, we implement a memory-bound GPU-based ultrasound simulation and evaluate the use of a technique for improving performance by compressing the data into a fixedpoint representation that reduces the time required for interhost-device transfers. We demonstrate a speedup of 1.5 times on a simulation where the data is broken into regions that must be copied back and forth between the CPU and GPU. We develop a model that can be used to determine the amount of temporal blocking required to achieve near optimal performance, without extensive experimentation. This technique may also be applied to GPU-based scientific simulations in other domains such as computational fluid dynamics and electromagnetic wave simulation.

Ultrasonic pulse propagation simulation using OpenCL for environment mapping and discovery

“…Rubi et al (2017) implemented and compared two simulation models for training, and Tobias et al (2009) used CUDA to simulate medical images. Multiple other authors used GPU-based ultrasound simulations (Haigh and McCreath, 2014; Jaros et al, 2012; Varray et al, 2011; Aguilar et al, 2013). Emmanuel et al (2002) simulated ultrasonic waves based on finite-difference time-domain computations of the elastodynamic equations.…”