Current microprocessors include hardware to optimize some specifics workloads.
In general, these hardware knobs are set on a default configuration on the booting
process of the machine. This default behavior cannot be beneficial for all types of
workloads and they are not controlled by anyone but the end user, who needs to
know what configuration is the best one for the workload running. Some of these
knobs are: (1) the Simultaneous MultiThreading level, which specifies the number
of threads that can run simultaneously on a physical CPU, and (2) the data
prefetch engine, that manages the prefetches on memory. Parallel programming
models are here to stay, and one programming model that succeed in allowing programmers
to easily parallelize applications is Open Multi Processing (OMP). Also,
the architecture of microprocessors is getting more complex that end users cannot
afford to optimize their workloads for all the architectural details. These architectural
knobs can help to increase performance but it is needed an automatic and
adaptive system managing them. In this work we propose an independent library
for OpenMP runtimes to increase performance up to 220% (14.7% on average)
while reducing dynamic power consumption up to 13% (2% on average) on a real
POWER8 processor
