Most embedded devices are based on heterogeneous Multiprocessor System on Chips
(MPSoCs). These contain a variety of processors like CPUs, micro-controllers, DSPs,
GPUs and specialised accelerators. The heterogeneity of these systems helps in achieving
good performance and energy efficiency but makes programming inherently difficult.
There is no single programming language or runtime to program such platforms.
This thesis makes three contributions to these problems. First, it presents a framework
that allows code in Single Program Multiple Data (SPMD) form to be mapped
to a heterogeneous platform. The mapping space is explored, and it is shown that the
best mapping depends on the metric used.
Next, a compiler framework is presented which bridges the gap between the high
-level programming model of OpenMP and the heterogeneous resources of MPSoCs.
It takes OpenMP programs and generates code which runs on all processors. It delivers
programming ease while exploiting heterogeneous resources.
Finally, a compiler-based approach to runtime power management for heterogeneous
cores is presented. Given an externally provided budget, the approach generates
heterogeneous, partitioned code that attempts to give the best performance within that
budget
