CUDACPP gives MadGraph data-parallel helicity amplitudes, delivering linear SIMD CPU speed-ups and up to order-of-magnitude GPU speed-ups for high-multiplicity QCD event generation.
PDFFlow: parton distribution functions on GPU
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abstract
We present PDFFlow, a new software for fast evaluation of parton distribution functions (PDFs) designed for platforms with hardware accelerators. PDFs are essential for the calculation of particle physics observables through Monte Carlo simulation techniques. The evaluation of a generic set of PDFs for quarks and gluon at a given momentum fraction and energy scale requires the implementation of interpolation algorithms as introduced for the first time by the LHAPDF project. PDFFlow extends and implements these interpolation algorithms using Google's TensorFlow library providing the capabilities to perform PDF evaluations taking fully advantage of multi-threading CPU and GPU setups. We benchmark the performance of this library on multiple scenarios relevant for the particle physics community.
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Data-parallel leading-order event generation in MadGraph5_aMC@NLO
CUDACPP gives MadGraph data-parallel helicity amplitudes, delivering linear SIMD CPU speed-ups and up to order-of-magnitude GPU speed-ups for high-multiplicity QCD event generation.