
Directive-based GPU programming models are gaining momentum, since they transparently relieve programmers from dealing with complexity of low-level GPU programming, which often reflects the underlying architecture. However, too much abstraction in directive models puts a significant burden on programmers for debugging applications and tuning performance. In this paper, we propose a directive-based, interactive program debugging and optimization system. This system enables intuitive and synergistic interaction among programmers, compilers, and runtimes for more productive and efficient GPU computing. We have designed and implemented a series of prototype tools within our new open source compiler framework, called Open Accelerator Research Compiler (Open ARC), Open ARC supports the full feature set of Opencast V1.0. Our evaluation on twelve Open ACC benchmarks demonstrates that our prototype debugging and optimization system can detect a variety of translation errors. Additionally, the optimization provided by our prototype minimizes memory transfers, when compared to a fully manual memory management scheme.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
