This chapter uses two scientific computing kernels to illustrate challenges of designing parallel algorithms for one heterogeneous multi-core processor, the Cell Broadband Engine processor (Cell/B.E.). It describes the limitation of the current parallel systems using single-core processors as building blocks. The limitation deteriorates the performance of applications which have data-intensive and computationintensive kernels such as Finite Difference Time Domain (FDTD) and Fast Fourier Transform (FFT). FDTD is a regular problem with nearest neighbour comminuncation pattern under synchronization constraint. FFT based on indirect swap network (ISN) modifies the data mapping in traditional Cooley- Tukey butterfly network to improve data locality, hence reducing the communication and synchronization overhead. The authors hope to unleash the Cell/B.E. and design parallel FDTD and parallel FFT based on ISN by taking into account unique features of Cell/B.E. such as its eight SIMD processing units on the single chip and its high-speed on-chip bus.
dispel4py: A Python Framework for Data-Intensive Scientific Computing
