With the modern chip design
facing the so called frequency, power and other walls, multi-core
systems have become dominant. Due to the relatively large operating cost
of fine-grained parallelism, the systems are often task-oriented.

With
the recent appearance of more synchronous platforms for parallel
computing, we propose a language supported task system optimization for
strictly synchronous multi-core architectures equipped with hardware
accelerated multi-prefix operations and other finite resources (with
respect to concurrent access). The purpose of this system is to
dynamically manage the error prone allocation of such resources, yet
provide reasonable performance speedups without placing the burden of
resource management to the programmer. Our system compiles several
specialized versions of accelerated functions that are dynamically
picked by the runtime task system based on the tasks' requirements and
the resource availability.