scholarly journals Hardware-accelerated Simulation-based Inference of Stochastic Epidemiology Models for COVID-19

2022 ◽  
Vol 18 (2) ◽  
pp. 1-24
Sourabh Kulkarni ◽  
Mario Michael Krell ◽  
Seth Nabarro ◽  
Csaba Andras Moritz

Epidemiology models are central to understanding and controlling large-scale pandemics. Several epidemiology models require simulation-based inference such as Approximate Bayesian Computation (ABC) to fit their parameters to observations. ABC inference is highly amenable to efficient hardware acceleration. In this work, we develop parallel ABC inference of a stochastic epidemiology model for COVID-19. The statistical inference framework is implemented and compared on Intel’s Xeon CPU, NVIDIA’s Tesla V100 GPU, Google’s V2 Tensor Processing Unit (TPU), and the Graphcore’s Mk1 Intelligence Processing Unit (IPU), and the results are discussed in the context of their computational architectures. Results show that TPUs are 3×, GPUs are 4×, and IPUs are 30× faster than Xeon CPUs. Extensive performance analysis indicates that the difference between IPU and GPU can be attributed to higher communication bandwidth, closeness of memory to compute, and higher compute power in the IPU. The proposed framework scales across 16 IPUs, with scaling overhead not exceeding 8% for the experiments performed. We present an example of our framework in practice, performing inference on the epidemiology model across three countries and giving a brief overview of the results.

2019 ◽  
Timothy O. West ◽  
Luc Berthouze ◽  
Simon F. Farmer ◽  
Hayriye Cagnan ◽  
Vladimir Litvak

AbstractBrain networks and the neural dynamics that unfold upon them are of great interest across the many scales of systems neuroscience. The tools of inverse modelling provide a way of both constraining and selecting models of large scale brain networks from empirical data. Such models have the potential to yield broad theoretical insights in the understanding of the physiological processes behind the integration and segregation of activity in the brain. In order to make inverse modelling computationally tractable, simplifying model assumptions have often been adopted that appeal to steady-state approximations to neural dynamics and thus prevent the investigation of stochastic or intermittent dynamics such as gamma or beta burst activity. In this work we describe a framework that uses the Approximate Bayesian Computation (ABC) algorithm for the inversion of neural models that can flexibly represent any statistical feature of empirically recorded data and eschew the need to assume a locally linearized system. Further, we demonstrate how Bayesian model comparison can be applied to fitted models to enable the selection of competing hypotheses regarding the causes of neural data. This work establishes a validation of the procedures by testing for both the face validity (i.e. the ability to identify the original model that has generated the observed data) and predictive validity (i.e. the consistency of the parameter estimation across multiple realizations of the same data). From the validation and example applications presented here we conclude that the proposed framework provides a novel opportunity to researchers aiming to explain how complex brain dynamics emerge from neural circuits.

2013 ◽  
Vol 380-384 ◽  
pp. 1652-1655
Zhang Yang ◽  
Chen Wen Bo ◽  
Bai Qi Feng ◽  
Lian Li

GPU computing is the use of a graphics processing unit together with a CPU to accelerate large scale scientific and engineering applications, such as molecule simulation. The paper use NVIDIA Tesla C2050NVIDIA GTX580 and NAMD 2.9 simulates three differences molecule systems: Beta2,SET9 and Ubiquitin. We compared and analyzed the results of the simulations experiment, and come to conclusion that the difference molecule systems will get the difference speed accelerated. The computing times of four GPU is nearly half of the time used by one GPU; and this is especially in the case of macromolecules system. Furthermore, from the GPUs memory utilization rate, the larger the protein system is, the higher the memory use of the GPU is. The performance of NVIDIA GTX580 is only half of the NVIDIAC2050. NVIDIA Tesla C2050 is can satisfy an even larger system simulation.

2018 ◽  
Vol 33 (1) ◽  
pp. 4-18 ◽  
Trevelyan J. McKinley ◽  
Ian Vernon ◽  
Ioannis Andrianakis ◽  
Nicky McCreesh ◽  
Jeremy E. Oakley ◽  

2017 ◽  
Vol 469 (3) ◽  
pp. 2791-2805 ◽  
ChangHoon Hahn ◽  
Mohammadjavad Vakili ◽  
Kilian Walsh ◽  
Andrew P. Hearin ◽  
David W. Hogg ◽  

VASA ◽  
2020 ◽  
pp. 1-6
Hanji Zhang ◽  
Dexin Yin ◽  
Yue Zhao ◽  
Yezhou Li ◽  
Dejiang Yao ◽  

Summary: Our meta-analysis focused on the relationship between homocysteine (Hcy) level and the incidence of aneurysms and looked at the relationship between smoking, hypertension and aneurysms. A systematic literature search of Pubmed, Web of Science, and Embase databases (up to March 31, 2020) resulted in the identification of 19 studies, including 2,629 aneurysm patients and 6,497 healthy participants. Combined analysis of the included studies showed that number of smoking, hypertension and hyperhomocysteinemia (HHcy) in aneurysm patients was higher than that in the control groups, and the total plasma Hcy level in aneurysm patients was also higher. These findings suggest that smoking, hypertension and HHcy may be risk factors for the development and progression of aneurysms. Although the heterogeneity of meta-analysis was significant, it was found that the heterogeneity might come from the difference between race and disease species through subgroup analysis. Large-scale randomized controlled studies of single species and single disease species are needed in the future to supplement the accuracy of the results.

Angela Dranishnikova

In the article, the author reflects the existing problems of the fight against corruption in the Russian Federation. He focuses on the opacity of the work of state bodies, leading to an increase in bribery and corruption. The topic we have chosen is socially exciting in our days, since its significance is growing on a large scale at all levels of the investigated aspect of our modern life. Democratic institutions are being jeopardized, the difference in the position of social strata of society in society’s access to material goods is growing, and the state of society is suffering from the moral point of view, citizens are losing confidence in the government, and in the top officials of the state.

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