Programs written for GPUs often contain correctness errors such as races, deadlocks, or
may compute the wrong result. Existing debugging tools often miss these errors because of …

While Monte Carlo Neutron Transport (MCNT) is near-embarrasingly parallel, the effectively
unpredictable lifetime of neutrons can lead to divergence when MCNT is evaluated on …

OpenCL has been designed to achieve functional portability across multi-core devices from
different vendors. However, the lack of a single cross-target optimizing compiler severely …

OpenCL has become the de-facto data parallel programming model for parallel devices in
today's high-performance supercomputers. OpenCL was designed with the goal of …

We address the problem of applying powerful pattern recognition algorithms based on
kernels to efficient visual tracking. Recently S. Avidan,(2001) has shown that object …

Modern throughput processors such as GPUs achieve high performance and efficiency by
exploiting data parallelism in application kernels expressed as threaded code. One draw …

If-conversion is a fundamental technique for vectorization. It accounts for the fact that in a
SIMD program, several targets of a branch might be executed because of divergence …

Function merging is an important optimization for reducing code size. This technique
eliminates redundant code across functions by merging them into a single function. While …

Resource-constrained devices for embedded systems are becoming increasingly important.
In such systems, memory is highly restrictive, making code size in most cases even more …

GPGPUs use the Single-Instruction-Multiple-Thread (SIMT) execution model where a group
of threads—wavefront or warp—execute instructions in lockstep. When threads in a group …