scholarly journals Aging at the spin-glass/ferromagnet transition: Monte Carlo simulations using graphics processing units

2015 ◽  
Vol 91 (17) ◽  
Author(s):  
Markus Manssen ◽  
Alexander K. Hartmann
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Spin Glass ◽  
Graphics Processing Units ◽  
Graphics Processing

scholarly journals Molecular Monte Carlo Simulations Using Graphics Processing Units: To Waste Recycle or Not?

2011 ◽  
Vol 7 (10) ◽  
pp. 3208-3222 ◽  
Author(s):  
Jihan Kim ◽  
Jocelyn M. Rodgers ◽  
Manuel Athènes ◽  
Berend Smit
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Graphics Processing Units ◽  
Graphics Processing

Monte Carlo Simulations of Spin Glass Systems on the Cell Broadband Engine

2010 ◽  
pp. 467-476 ◽  
Author(s):  
Francesco Belletti ◽  
Marco Guidetti ◽  
Andrea Maiorano ◽  
Filippo Mantovani ◽  
Sebastiano Fabio Schifano ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Spin Glass ◽  
Cell Broadband Engine

scholarly journals XVA PRINCIPLES, NESTED MONTE CARLO STRATEGIES, AND GPU OPTIMIZATIONS

2018 ◽  
Vol 21 (06) ◽  
pp. 1850030 ◽  
Author(s):  
LOKMAN A. ABBAS-TURKI ◽  
STÉPHANE CRÉPEY ◽  
BABACAR DIALLO
Keyword(s):  
Monte Carlo ◽  
Interest Rate ◽  
Outer Layer ◽  
Graphics Processing Units ◽  
Lower Layer ◽  
Credit Derivatives ◽  
Square Root ◽  
Root Number ◽  
Graphics Processing ◽  
Gpu Implementation

We present a nested Monte Carlo (NMC) approach implemented on graphics processing units (GPUs) to X-valuation adjustments (XVAs), where X ranges over C for credit, F for funding, M for margin, and K for capital. The overall XVA suite involves five compound layers of dependence. Higher layers are launched first, and trigger nested simulations on-the-fly whenever required in order to compute an item from a lower layer. If the user is only interested in some of the XVA components, then only the sub-tree corresponding to the most outer XVA needs be processed computationally. Inner layers only need a square root number of simulation with respect to the most outer layer. Some of the layers exhibit a smaller variance. As a result, with GPUs at least, error-controlled NMC XVA computations are doable. But, although NMC is naively suited to parallelization, a GPU implementation of NMC XVA computations requires various optimizations. This is illustrated on XVA computations involving equities, interest rate, and credit derivatives, for both bilateral and central clearing XVA metrics.

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