  Computing systems have become increasingly complex with the emergence of
heterogeneous hardware combining multicore CPUs and GPUs. These parallel
systems exhibit tremendous computational power at the cost of increased
programming effort. This results in a tension between achieving performance and
code portability. Code is either tuned using device-specific optimizations to
achieve maximum performance or is written in a high-level language to achieve
portability at the expense of performance.
  We propose a novel approach that offers high-level programming, code
portability and high-performance. It is based on algorithmic pattern
composition coupled with a powerful, yet simple, set of rewrite rules. This
enables systematic transformation and optimization of a high-level program into
a low-level hardware specific representation which leads to high performance
code.
  We test our design in practice by describing a subset of the OpenCL
programming model with low-level patterns and by implementing a compiler which
generates high performance OpenCL code. Our experiments show that we can
systematically derive high-performance device-specific implementations from
simple high-level algorithmic expressions. The performance of the generated
OpenCL code is on par with highly tuned implementations for multicore CPUs and
GPUs written by experts
