Leveraging Hardware Probes and Optimizations for Accelerating Fuzz Testing of Heterogeneous Applications

Abstract

There is a growing interest in the computer architecture community to incorporate heterogeneity and specialization to improve performance. Developers can create heterogeneous applications that consist of both host code and kernel code, where compute-intensive kernels can be offloaded from CPU to hardware accelerators. Testing such applications on real heterogeneous architectures is extremely challenging as kernels are black boxes, providing no information about the kernels’ internal execution to diagnose issues such as silent hangs or unexpected results. Additionally, inputs for heterogeneous applications are often large matrices, leading to a vast search space for identifying bug-revealing inputs.