2 citations · 3 across the 8 of their papers we have counts for
9 papers
Advancing RT Core-Accelerated Fixed-Radius Nearest Neighbor Search
Enzo Meneses, Hugo Bec, Cristóbal A. Navarro +5
In this work we introduce three ideas that can further improve particle FRNN physics simulations running on RT Cores; i) a real-time update/rebuild ratio optimizer for the bounding…
CAT: Cellular Automata on Tensor cores
Cristóbal A. Navarro, Felipe A. Quezada, Enzo Meneses +2
Cellular automata (CA) are simulation models that can produce complex emergent behaviors from simple local rules. Although state-of-the-art GPU solutions are already fast due to th…
RaViTT: Random Vision Transformer Tokens
Felipe A. Quezada, Carlos F. Navarro, Cristian Muñoz +5
Vision Transformers (ViTs) have successfully been applied to image classification problems where large annotated datasets are available. On the other hand, when fewer annotations a…
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…
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…
Modeling GPU Dynamic Parallelism for Self Similar Density Workloads
Felipe A. Quezada, Cristóbal A. Navarro, Miguel Romero +1
Dynamic Parallelism (DP) is a runtime feature of the GPU programming model that allows GPU threads to execute additional GPU kernels, recursively. Apart from making the programming…
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…
Efficient GPU Thread Mapping on Embedded 2D Fractals
Cristóbal A. Navarro, Felipe A. Quezada, Nancy Hitschfeld +2
This work proposes a new approach for mapping GPU threads onto a family of discrete embedded 2D fractals. A block-space map $λ: \mathbb{Z}_{\mathbb{E}}^{2} \mapsto \mathbb{Z}_{\mat…