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For parallelism to become tractable for mass programmers, shared-memory languages and environments must evolve to enforce disciplined practices that ban "wild shared-memory behaviors;'' e.g., unstructured parallelism, arbitrary data races, and ubiquitous non-determinism. This software evolution is a rare opportunity for hardware designers to rethink(More)
The k-D tree is a well-studied acceleration data structure for ray tracing. It is used to organize primitives in a scene to allow efficient execution of intersection operations between rays and the primitives. The highest quality k-D tree can be obtained using greedy cost optimization based on a surface area heuristc (SAH). While the high quality enables(More)
Continued technology scaling is resulting in systems with billions of devices. Unfortunately, these devices are prone to failures from various sources, resulting in even commodity systems being affected by the growing reliability threat. Thus, traditional solutions involving high redundancy or piecemeal solutions targeting specific failure modes will no(More)
Continued technology scaling is resulting in systems with billions of devices. Consequently, these devices are are prone to failures from various sources resulting in a growing reliability threat. As this reliability problem is expected to affect the broad computing market, traditional solutions involving high redundancy, or piecemeal solutions targeting(More)
We believe that future large-scale multicore systems will require disciplined parallel programming practices, including data-race-freedom, deterministic-by-default semantics, and structured, explicit parallel control and side-effects. We argue that this software evolution presents far-reaching opportunities for parallel hardware design to greatly improve(More)
The k-D tree is a well-studied acceleration data structure for ray tracing. It is used to organize primitives in a scene to allow efficient execution of intersection operations between rays and the primitives. The highest quality k-D tree can be obtained using greedy cost optimization based on a surface area heuristc (SAH). While the high quality enables(More)
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