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Accelerating Range Minimum Queries with Ray Tracing Cores
Enzo Meneses, Cristóbal A. Navarro, Héctor Ferrada +1
During the last decade GPU technology has shifted from pure general purpose computation to the inclusion of application specific integrated circuits (ASICs), such as Tensor Cores a…
Accelerating the Convex Hull Computation with a Parallel GPU Algorithm
Alan Keith, Héctor Ferrada, Cristóbal A. Navarro
The convex hull is a fundamental geometrical structure for many applications where groups of points must be enclosed or represented by a convex polygon. Although efficient sequenti…
A Scalable and Energy Efficient GPU Thread Map for m-Simplex Domains
Cristóbal A. Navarro, Felipe A. Quezada, Benjamin Bustos +2
This work proposes a new GPU thread map for -simplex domains, that scales its speedup with dimension and is energy efficient compared to other state of the art approaches. The m…
GGArray: A Dynamically Growable GPU Array
Enzo Meneses, Cristóbal A. Navarro, Héctor Ferrada
We present a dynamically Growable GPU array (GGArray) fully implemented in GPU that does not require synchronization with the host. The idea is to improve the programming of GPU ap…
Squeeze: Efficient Compact Fractals for Tensor Core GPUs
Felipe A. Quezada, Cristóbal A. Navarro, Nancy Hitschfeld +1
This work presents Squeeze, an efficient compact fractal processing scheme for tensor core GPUs. By combining discrete-space transformations between compact and expanded forms, one…
Accelerating Compact Fractals with Tensor Core GPUs
Felipe A. Quezada, Cristóbal A. Navarro
This work presents a GPU thread mapping approach that allows doing fast parallel stencil-like computations on discrete fractals using their compact representation. The intuition be…