Formal Methods for High Integrity GPU Software Development and Verification

Modern safety critical systems require high levels of performance for advanced functionalities, which are not possible with the simple conventional architectures currently used in them. Embedded General Purpose Graphics Processing Units (GPG-PUs) are among the hardware technologies which can provide the high performance required in these domains. However, their massively parallel nature complicates the verification of their software and increases its cost because it usually involves code coverage through extensive human-driven testing. The Ada SPARK language has traditionally been used in highly-critical environments for its formal verification capabilities and powerful type system. The use of such tools which are backed up by theorem provers, has significantly lowered the amount of effort needed to validate functionality of safety-critical systems. In this European Space Agency (ESA) funded project, we utilize AdaCore's CUDA backend for Ada in conjunction with the SPARK language subset to assess the state of static verification for GPU kernels. We assess the error detection capabilities of the available tools and we formulate a methodology to maximise their effectiveness. Moreover, our project results using ESA's open source GPU4S Benchmarking suite show that common programming mistakes in GPU software development can be prevented.