Heterogeneous computing: Challenges and opportunities

Anytime you work with oranges and apples, you’ll need a number of schemes to organize total performance. This article surveys the challenges posed by H omogeneous computing, which uses one or more machines of the same type, has provided adequate performance for many applications in the past. Many of these applications had more than one type of embedded parallelism, such as single instruction, multiple data (SIMD) and multiple instruc-tion, multiple data (MIMD). Most of the current parallel machines are suited only for homogeneous computing. However, numerous applications that have more than one type of embedded parallelism are now being considered for parallel implementation. On the other hand, as the amount of homogeneous parallelism in applications decreases, homogeneous systems cannot offer the desired speedups. To exploit the heterogeneity in computations, researchers are investigating a suit