Handling task dependencies under strided and aliased references

The emergence of multicore processors has increased the need for simple parallel programming models usable by nonexperts. The ability to specify subparts of a bigger data structure is an important trait of High Productivity Programming Languages. Such a concept can also be applied to dependency-aware task-parallel programming models. In those paradigms, tasks may have data dependencies, and those are used for scheduling them in parallel. However, calculating dependencies between subparts of bigger data structures is challenging. Accessed data may be strided, and can fully or partially overlap the accesses of other tasks. Techniques that are too approximate may produce too many extra dependencies and limit parallelism. Techniques that are too precise may be impractical in terms of time and space. We present the abstractions, data structures and algorithms to calculate dependencies between tasks with strided and possibly different memory access patterns. Our technique is performed at r...

• Type: Conference
• Year: 2010
• Where: ICS
• Authors: Josep M. Pérez, Rosa M. Badia, Jesús Labarta
• Keywords: Bigger Data Structures, Data Structures, ICS 2010, Programming Models