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Over the past years GPUs have been successfully applied to the task of inverting the fermion matrix in lattice QCD calculations. Even strong scaling to capability-level supercomputers, corresponding to O(100) GPUs or more has been achieved. However strong scaling a whole gauge field generation algorithm to this regim requires significantly more functionality than just having the matrix inverter utilizing the GPUs and has not yet been accomplished. This contribution extends QDP-JIT, the migration of SciDAC QDP++ to GPU-enabled parallel systems, to help to strong scale the whole Hybrid Monte-Carlo to this regime. Initial results are shown for gauge field generation with Chroma simulating pure Wilson fermions on OLCF TitanDev.
Large language models have led to state-of-the-art accuracies across a range of tasks. However, training these models efficiently is challenging for two reasons: a) GPU memory capacity is limited, making it impossible to fit large models on even a mu
The classical method of determining the atomic structure of complex molecules by analyzing diffraction patterns is currently undergoing drastic developments. Modern techniques for producing extremely bright and coherent X-ray lasers allow a beam of s
We describe our experience porting the Regensburg implementation of the DD-$alpha$AMG solver from QPACE 2 to QPACE 3. We first review how the code was ported from the first generation Intel Xeon Phi processor (Knights Corner) to its successor (Knight
The Kernel Polynomial Method (KPM) is a well-established scheme in quantum physics and quantum chemistry to determine the eigenvalue density and spectral properties of large sparse matrices. In this work we demonstrate the high optimization potential
We consider the implementation of a parallel Monte Carlo code for high-performance simulations on PC clusters with MPI. We carry out tests of speedup and efficiency. The code is used for numerical simulations of pure SU(2) lattice gauge theory at ver