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Graphics processor units (GPUs) today can be
used for computations that go beyond graphics and such use
can attain a performance that is orders of magnitude greater
than a normal processor. The software executing on a graphics
processor is composed of a set of (often thousands of) threads
which operate on different parts of the data and thereby
jointly compute a result which is delivered to another thread
executing on the main processor. Hence the response time of
a thread executing on the main processor is dependent on the
finishing time of the execution of threads executing on the GPU.
Therefore, we present a simple method for calculating an upper
bound on the finishing time of threads executing on a GPU, in
particular NVIDIA Fermi. Developing such a method is nontrivial
because threads executing on a GPU share hardware
resources at very fine granularity.