Craig J. Webb

Computing room acoustics with CUDA - 3D FDTD schemes with boundary losses and viscosity

In seeking to model realistic room acoustics, direct numerical simulation can be employed. This paper presents 3D Finite Difference Time Domain schemes that incorporate losses at boundaries and due to the viscosity of air. These models operate within a virtual room designed on a detailed floor plan. The schemes are computed at 44.1kHz, using large-scale data sets containing up to 100 million points each. A performance comparison is made between serial computation in C, and parallel computation using CUDA on GPUs, showing up to 80 times speed-ups. Testing on two different Nvidia Tesla cards shows the benefits of the latest FERMI architecture for double precision floating-point computation.

Large-scale virtual acoustics simulation at audio rates using three dimensional finite difference time domain and multiple graphics processing units

The computation of large-scale virtual acoustics using the 3D finite difference time domain (FDTD) is prohibitively computationally expensive, especially at high audio sample rates, when using traditional CPUs. In recent years the computer gaming industry has driven the development of extremely powerful Graphics Processing Units (GPUs). Through specialised development and tuning we can exploit the highly parallel GPU architecture to make such FDTD computations feasible.This paper describes the simultaneous use of multiple NVIDIA GPUs to compute schemes containing over a billion grid points. We examine the use of asynchronous halo transfers between cards, to hide the latency involved in transferring data,and overall computation time is considered with respect to variation in the size of the partition layers. As hardware memory poses limitations on the size of the room to be rendered, we also investigate the use of single precision arithmetic.This allows twice the domain space, compared with double precisio...