High-Level GPU Multi-purpose Profiler

The graphics processing units (GPUs) have become an integral part of today´s computing systems. They have risen and evolved over the last years, becoming a platform for parallel computation with a large number of scalar processors and abundant memory bandwidth. They deliver high standard computation performance, but also require a lot of power supplies and cooling systems. Its rapid increase in both programmability and capability has allowed a powerful research community to arise - they have managed to successfully map out a broad range of computationally demanding, complex problems to the GPU. This paper presents a high-level GPU multi-purpose profiler using several general methods which can analyze not only the given source code, but also the run-time binary application. These models obtain the GPU running time, memory space used and the general flow of the application and, more importantly, it provides a platform on which further new metrics can be implemented.