Quantum Monte Carlo algorithms: making most of large-scale multi/many-core clusters
نویسندگان
چکیده
With advances in algorithms and the changing landscape of high performance computers (HPC), the quantum Monte Carlo method has become a leading contender for high accuracy calculations for the electronic structure of realistic systems. QMC, being statistical, is naturally scalable to a large number of processors. We discuss QMC implementations to overcome the important efficiency and scalability bottlenecks encountered with the HPC systems based on the multi/many-core architecture of today and present state-of-art QMC calculations of solid-state and molecular systems using tens or hundred thousand cores on the petascale computers. Also presented are the solutions for QMC to adapt to the future HPC architectures and to harness ever-increasing computing powers to tackle outstanding materials and chemical
منابع مشابه
Hybrid algorithms in quantum Monte Carlo
With advances in algorithms and growing computing powers, quantum Monte Carlo (QMC) methods have become a leading contender for high accuracy calculations for the electronic structure of realistic systems. The performance gain on recent HPC systems is largely driven by increasing parallelism: the number of compute cores of a SMP and the number of SMPs have been going up, as the Top500 list atte...
متن کاملFully accelerating quantum Monte Carlo simulations of real materials on GPU clusters
Continuum quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting the properties of matter from fundamental principles. By solving the manybody Schrödinger equation through a stochastic projection, it achieves greater accuracy than mean-field methods and better scalability than quantum chemical methods, enabling scientific discovery across a broad spectrum of disciplines. T...
متن کاملQuantum monte carlo for large chemical systems: Implementing efficient strategies for petascale platforms and beyond
Various strategies to implement efficiently quantum Monte Carlo (QMC) simulations for large chemical systems are presented. These include: (i) the introduction of an efficient algorithm to calculate the computationally expensive Slater matrices. This novel scheme is based on the use of the highly localized character of atomic Gaussian basis functions (not the molecular orbitals as usually done)...
متن کاملArchitectural Comparisons for a Quantum Monte Carlo Application
Recent technological advances have led to a number of emerging platforms such as multi-cores, reconfigurable computing, and graphics processing units. We present a comparative study of multi-cores, field-programmable gate arrays, and graphics processing units for a Quantum Monte Carlo chemistry application. The speedups of these implementations are measured relative to a multi-core implementati...
متن کاملEnhancing Parallelism in Monte Carlo Techniques for Solving Large Sparse Linear Systems
The problem of solving large scale sparse linear systems arises in many scientific and engineering applications. Recent advances in multicore processors and clusters that consist of hundreds of thousands of cores motivate new techniques to solve such problems efficiently. Two main design considerations are the accuracy of the solution and the scalability of the method, which compete against eac...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010