Tanya Amert

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The push towards fielding autonomous-driving capabilities in vehicles is happening at breakneck speed. Semi-autonomous features are becoming increasingly common, and fully autonomous vehicles are optimistically forecast to be widely available in just a few years. Today, graphics processing units (GPUs) are seen as a key technology in this push towards(More)
Embedded systems augmented with graphics processing units (GPUs) are seeing increased use in safety-critical real-time systems such as autonomous vehicles. Due to monetary cost requirements along with size, weight, and power (SWaP) constraints, embedded GPUs are often computationally impoverished compared to those used in non-embedded systems. In order to(More)
In prior work on multiprocessor real-time locking protocols, only protocols within the RNLP family support unrestricted lock nesting while guaranteeing asymptotically optimal priority-inversion blocking bounds. However, these protocols support nesting at the expense of increasing the cost of processing non-nested lock requests, which tend to be the common(More)
NVIDIA’s CUDA API has enabled GPUs to be used as computing accelerators across a wide range of applications. This has resulted in performance gains in many application domains, but the underlying GPU hardware and software are subject to many nonobvious pitfalls. This is particularly problematic for safety-critical systems, where worst-case behaviors must be(More)
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