Customizing FFT with FMA for China Accelerator

Abstract

Recently, Fast Fourier Transform (FFT) was introduced to study pattern characterization in textiles. Accelerators are a promising platform to accelerate large-scale FFT computation. However, current accelerating FFT only uses the accelerator to compute, but uses a CPU as a mere task controller. Additionally, a specified interface for FFT is built into the China accelerator (CA), which severely restricts FFT parallelization and performance. Hence, we transform four multiplications and six additions into six Fused Multiply Add (FMA) operations, then reduce total float operations by 40%, assisted by FMAs equipped with a Vector Processing Unit (VPE). Moreover, we propose an Interface Adapter (IA) to cater to a specified interface and a Fused Algorithm for Interface Adapter (FAIA) to fully use both the CA and CPU to compute large-scale FFT with coordination. Experimental results validated successful performance.