Accelerated test execution using GPUs

Abstract

As product life-cycles become shorter and the scale and complexity of systems increase, accelerating the execution of large test suites gains importance. Existing research has primarily focussed on techniques that reduce the size of the test suite. By contrast, we propose a technique that accelerates test execution, allowing test suites to run in a fraction of the original time, by parallel execution with a Graphics Processing Unit (GPU). Program testing, which is in essence execution of the same program with multiple sets of test data, naturally exhibits the kind of data parallelism that can be exploited with GPUs. Our approach simultaneously executes the program with one test case per GPU thread. GPUs have severe limitations, and we discuss these in the context of our approach and define the scope of our applications. We observe speed-ups up to a factor of 27 compared to single-core execution on conventional CPUs with embedded systems benchmark programs