Search Results for "gpu faster"

Fast FDTD solver with graphics card support. Optimized for nanoscale optics - scanning near field optical microscopy, rough surface scattering and solar cells. Uses CUDA environment for graphics card operation.

Structures of arrays (SoA) are generally faster than arrays of structures (AoS) while AoS are more handy. This project (SoAx) combines the advantages of both. By means of C++(11) meta-template programming SoAx achieves maximal performance (efficient use of vector units and cache of modern CPUs) while providing a very convenient user interface (including object-oriented element handling) and flexibility. It has been designed to handle list-like sets of particles (similar to struct {int id;...

Latest Code on GitHub: https://github.com/aquaskyline/SOAP3-dp SOAP3-dp, through leveraging the computational power of both CPU and GPU with optimized algorithms, delivers high speed and sensitivity simultaneously. Compared with widely adopted aligners including BWA, Bowtie2, SeqAlto, CUSHAW2, GEM and GPU-based aligners BarraCUDA and CUSHAW, SOAP3-dp was found to be two to tens of times faster, while maintaining the highest sensitivity and lowest false discovery rate (FDR) on Illumina reads with different lengths. ...

Latest Code in GitHub: https://github.com/aquaskyline/MICA-aligner To better utilize MIC-enabled computers for NGS data analysis, we developed a new short-read aligner MICA that is optimized in view of MIC’s limitation and the extra parallelism inside each MIC core. Experiments on aligning 150bp paired-end reads show that MICA using one MIC board is ~4.85 times faster than the CPU-(multi-core)-based BWA-MEM and about the same speed as the GPU-based SOAP3-dp. Furthermore, MICA’s simplicity allows very efficient scale-up when multiple MIC boards are used in a node (3 cards gives a 14-fold speedup over 6-core BWA-MEM).

SIMBUCA (before called Simonion) is a simulation package that simulates the motion of charged particles under the influence of Electric and/or Magnetic fields. What makes Simbuca unique is that you can choose to calculate the Coulomb interaction between ions on a Graphics cards which is much faster than calculating this on the conventional CPU (reducing the simulation time from years to days). Therefore Simbuca has been applied in various projects which required to understand the...

...Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. ...

Simulate the optical reflectance from an infinite turbid medium under an ideal oblique incidence optical source. Two versions are implemented: CPU and GPU. They both generate statistically the same results but GPU version works much faster.

Our project consist in porting positioning algorithms on a GPU. We will improve programs which are already working on CPU in order to make them compatible with the CUDA technology offered by Nvidia. The advantage of this technology is that it allows us to use massive multithreading and so make calculations go faster. Algorithms will be implemented in C++.