39 citations · 42 across the 11 of their papers we have counts for
11 papers
Leveraging Mathematical Reasoning of LLMs for Efficient GPU Thread Mapping
Jose Maureira, Cristóbal A. Navarro, Hector Ferrada +1
Mapping parallel threads onto non-box-shaped domains is a known challenge in GPU computing; efficient mapping prevents performance penalties from unnecessary resource allocation. C…
Structural Segmentation of the Minimum Set Cover Problem: Exploiting Universe Decomposability for Metaheuristic Optimization
Isidora Hernández, Héctor Ferrada, Cristóbal A. Navarro
The Minimum Set Cover Problem (MSCP) is a classical NP-hard combinatorial optimization problem with numerous applications in science and engineering. Although a wide range of exact…
Ray Tracing Cores for General-Purpose Computing: A Literature Review
Enzo Meneses, Cristóbal A. Navarro, Héctor Ferrada +2
Recent research on ray tracing cores has explored repurposing these cores to solve non-graphical problems by reformulating them as geometric queries, leveraging the inherent parall…
Convex Hull 3D Filtering with GPU Ray Tracing and Tensor Cores
Roberto Carrasco, Enzo Meneses, Hector Ferrada +2
In recent years, applications such as real-time simulations, autonomous systems, and video games increasingly demand the processing of complex geometric models under stringent time…
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…
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…
An Evaluation of GPU Filters for Accelerating the 2D Convex Hull
Roberto Carrasco, Héctor Ferrada, Cristóbal A. Navarro +1
The Convex Hull algorithm is one of the most important algorithms in computational geometry, with many applications such as in computer graphics, robotics, and data mining. Despite…
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…
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…
AliBI: An Alignment-Based Index for Genomic Datasets
Hector Ferrada, Travis Gagie, Tommi Hirvola +1
With current hardware and software, a standard computer can now hold in RAM an index for approximate pattern matching on about half a dozen human genomes. Sequencing technologies h…
Hybrid Indexes for Repetitive Datasets
H. Ferrada, T. Gagie, T. Hirvola +1
Advances in DNA sequencing mean databases of thousands of human genomes will soon be commonplace. In this paper we introduce a simple technique for reducing the size of conventiona…