Stack size estimation on machine-independent intermediate code for OpenCL kernels

Abstract

Stack size is an important factor in the mapping decision when dealing with embedded heterogeneous architectures, where fast memory is a scarce resource. Trying to map a kernel onto a device with insufficient memory may lead to reduced performance or even failure to run the kernel. OpenCL kernels are often compiled just-in-time, starting from the source code or an intermediate machine-independent representation. Precise stack size information, however, is only available in machine-dependent code. We provide a method for computing the stack size with sufficient accuracy on machine-independent code, given knowledge of the target ABI and register file architecture. This method can be applied to make mapping decisions early, thus avoiding to compile multiple times the code for each possible accelerator in a complex embedded heterogeneous system.