13 papers · ranked by Valyu relevance
Ashley I. Teufel, Claus O. Wilke
We present an accelerated algorithm to forward-simulate origin--fixation models. Our algorithm requires on average only about two fitness evaluations per fixed mutation, whereas traditional algorithms require, per one fixed mutation, a number of fitness evaluations on the order of the effective population size Ne. Our…
Peter L. Bartlett, Chris Junchi Li, Jingfeng Wu, Bin Yu
In the field of optimization, developing accelerated methods for solving minimax and fixed-point problems remains a fundamental challenge. This paper presents a novel family of dual accelerated algorithms that achieve optimal convergence rates for both minimax and fixed-point problems. By exploring new anchoring…
Gang Mei, Nengxiong Xu, Liangliang Xu
This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting fast k-nearest neighbors (kNN) search. In AIDW, it needs to find…
Xuan Zuo, Hui-Yan Li, Shan Gao, Pu Zhang + 2 more
Adaptive gradient algorithms have been successfully used in deep learning. Previous work reveals that adaptive gradient algorithms mainly borrow the moving average idea of heavy ball acceleration to estimate the first- and second-order moments of the gradient for accelerating convergence. However, Nesterov acceleration…
Michael Muehlebach, Michael I. Jordan
We exploit analogies between first-order algorithms for constrained optimization and non-smooth dynamical systems to design a new class of accelerated first-order algorithms for constrained optimization. Unlike Frank-Wolfe or projected gradients, these algorithms avoid optimization over the entire feasible set at each…
Felix Kallenborn, Fawaz Dabbaghie, Martin Steinegger, Bertil Schmidt
The continually increasing volume of sequence data results in a growing demand for fast implementations of core algorithms. Computation of pairwise alignments based on dynamic programming is an important part in many bioinformatics pipelines and a major contributor to overall runtime due to the associated quadratic…
Yaniv Swiel, Jean-Tristan Brandenburg, Mahtaab Hayat, Wenlong Carl Chen + 2 more
Genome-wide association studies (GWASs) analyse genetic variation over the genomes of many individuals in an attempt to identify single nucleotide polymorphisms (SNPs) associated with complex phenotypes. To capture a large amount of genetic variation and increase the chance of detecting associated SNPs, modern GWASs…
Xin Wang, Bin Zhang, Xu Cao, Fei Liu + 2 more
Fluorescence molecular tomography (FMT) with early-photons can improve the spatial resolution and fidelity of the reconstructed results. However, its computing scale is always large which limits its applications. In this paper, we introduced an acceleration strategy for the early-photon FMT with graphics processing…
Tim Anderson, Travis J. Wheeler
Sequence alignment lies at the heart of genome sequence annotation. While the BLAST suite of alignment tools has long held an important role in alignment-based sequence database search, greater sensitivity is achieved through the use of profile hidden Markov models (pHMMs). The Forward algorithm that provides much of…
Pranay Reddy Kommera, Vinay Ramakrishnaiah, Christine Sweeney, Jeffrey Donatelli + 1 more
'Jeffrey Donatelli' 'Petrus H. Zwart'] The paper presents efforts to accelerate the multitiered iterative phasing (MTIP) algorithm on contemporary graphics processing units (GPUs). Application portability is demonstrated by accelerating the MTIP algorithm on NVIDIA and AMD GPUs using a single codebase.
David S. Lawrie
Forward Wright-Fisher simulations are powerful in their ability to model complex demography and selection scenarios, but suffer from slow execution on the CPU, thus limiting their usefulness. The single-locus Wright-Fisher forward algorithm is, however, exceedingly parallelizable, with many steps which are so-called…
Paulo E. P. Burke, Luciano da F. Costa
Simulation of reaction systems has been employed along decades for a better understanding of such systems. However, the ever-growing gathering of biological data implied in larger and more complex models that are computationally challenging for current discrete-stochastic simulation methods. In this work, we propose a…
Jonas Latt, Christophe Coreixas, Joël Beny, Fang-Bao Tian
We present a novel, hardware-agnostic implementation strategy for lattice Boltzmann (LB) simulations, which yields massive performance on homogeneous and heterogeneous many-core platforms. Based solely on C++17 Parallel Algorithms, our approach does not rely on any language extensions, external libraries…