Tag: Monte Carlo
NVIDIA Tesla K20 Benchmark with Financial Applications
It is apparent that NVIDIA’s new Tesla K20Xm GPU gives a huge performance improvement for real-world applications – up to 1.9x in this example (very close to the theoretical peak: 2x).
High-Throughput parallel blind Virtual Screening using BINDSURF
Authors present BINDSURF, a novel VS methodology that scans the whole protein surface in order to find new hotspots, where ligands might potentially interact with, and which is implemented in last generation massively parallel GPU hardware, allowing fast processing of large ligand databases.
Large-scale Monte Carlo simulations on multiple Graphics Processing Units
In this study, the application of the two-dimensional direct simulation Monte Carlo (DSMC) method using an MPI-CUDA parallelization paradigm on Graphics Processing Units (GPUs) clusters is presented
Development of a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport
In this paper, we have successfully implemented the DPM Monte Carlo dose calculation package on GPU architecture under the NVIDIA CUDA platform. We have also tested the efficiency and accuracy of our GPU implementation with respect to the original sequential DPM code on the CPU in various testing cases
Accelerating Quantum Monte Carlo Simulations of Real Materials on GPU Clusters
More accurate than mean-field methods and more scalable than quantum chemical methods, continuum quantum Monte Carlo (QMC) is an invaluable tool for predicting the properties of matter from fundamental principles
Monte-Carlo Methods in Finance Using the Xcelerit SDK
This video demonstrates the benefits of using the Xcelerit platform to efficiently run Monte-Carlo simulations using multi-core CPUs and graphics processing units.
Large-scale Nanostructure Simulations from X-ray Scattering Data On Graphics Processor Clusters
X-ray scattering is a valuable tool for measuring the structural properties of materials used in the design and fabrication of energy-relevant nanodevices that are key to the reduction of carbon emissions.
q-state Potts model metastability study using optimized GPU-based Monte Carlo algorithms
We implemented a GPU-based parallel code to perform Monte Carlo simulations of the two-dimensional q-state Potts model
High-Throughput Characterization of Porous Materials Using Graphics Processing Units
We have developed a high-throughput graphics processing unit code that can characterize a large database of crystalline porous materials
hybrid MANTIS: a CPU-GPU Monte Carlo method for modeling indirect x-ray detectors with columnar scintillators
The computational modeling of medical imaging systems often requires obtaining a large number of simulated images with low statistical uncertainty which translates into prohibitive computing times. We describe a novel hybrid approach for Monte Carlo simulations that maximizes utilization of CPUs and GPUs in modern workstations. We apply the method to the modeling of indirect…
