scholarly journals Learning-accelerated Discovery of Immune-Tumour Interactions

2019 ◽  
Author(s):  
Jonathan Ozik ◽  
Nicholson Collier ◽  
Randy Heiland ◽  
Gary An ◽  
Paul Macklin
Keyword(s):  
Open Source ◽  
High Performance Computing ◽  
High Performance ◽  
Spatial Dynamics ◽  
Simulation Models ◽  
Scale Model ◽  
Agent Based ◽  
Extreme Scale ◽  
Cancer Immunotherapies ◽  
Performance Computing

We present an integrated framework for enabling dynamic exploration of design spaces for cancer immunotherapies with detailed dynamical simulation models on high-performance computing resources. Our framework combines PhysiCell, an open source agent-based simulation platform for cancer and other multicellular systems, and EMEWS, an open source platform for extreme-scale model exploration. We build an agent-based model of immunosurveillance against heterogeneous tumours, which includes spatial dynamics of stochastic tumour-immune contact interactions. We implement active learning and genetic algorithms using high-performance computing workflows to adaptively sample the model parameter space and iteratively discover optimal cancer regression regions within biological and clinical constraints.

scholarly journals Application-based fault tolerance techniques for sparse matrix solvers

2017 ◽  
Vol 32 (5) ◽  
pp. 627-640
Author(s):  
Simon McIntosh–Smith ◽  
Rob Hunt ◽  
James Price ◽  
Alex Warwick Vesztrocy
Keyword(s):  
Fault Tolerance ◽  
High Performance Computing ◽  
High Performance ◽  
Sparse Matrix ◽  
Sparse Matrices ◽  
Error Correcting Codes ◽  
Computing Systems ◽  
Hardware Costs ◽  
Extreme Scale ◽  
Performance Computing

High-performance computing systems continue to increase in size in the quest for ever higher performance. The resulting increased electronic component count, coupled with the decrease in feature sizes of the silicon manufacturing processes used to build these components, may result in future exascale systems being more susceptible to soft errors caused by cosmic radiation than in current high-performance computing systems. Through the use of techniques such as hardware-based error-correcting codes and checkpoint-restart, many of these faults can be mitigated at the cost of increased hardware overhead, run-time, and energy consumption that can be as much as 10–20%. Some predictions expect these overheads to continue to grow over time. For extreme scale systems, these overheads will represent megawatts of power consumption and millions of dollars of additional hardware costs, which could potentially be avoided with more sophisticated fault-tolerance techniques. In this paper we present new software-based fault tolerance techniques that can be applied to one of the most important classes of software in high-performance computing: iterative sparse matrix solvers. Our new techniques enables us to exploit knowledge of the structure of sparse matrices in such a way as to improve the performance, energy efficiency, and fault tolerance of the overall solution.

scholarly journals Inspiring the Next Generation of HPC Engineers with Reconfigurable, Multi-Tenant Resources for Teaching and Research

2021 ◽  
Vol 13 (21) ◽  
pp. 11782
Author(s):  
Taha Al-Jody ◽  
Hamza Aagela ◽  
Violeta Holmes
Keyword(s):  
Open Source ◽  
High Performance Computing ◽  
Systems Engineering ◽  
High Performance ◽  
Bare Metal ◽  
Next Generation ◽  
Teaching And Research ◽  
Exascale Computing ◽  
Secure Access ◽  
Performance Computing

There is a tradition at our university for teaching and research in High Performance Computing (HPC) systems engineering. With exascale computing on the horizon and a shortage of HPC talent, there is a need for new specialists to secure the future of research computing. Whilst many institutions provide research computing training for users within their particular domain, few offer HPC engineering and infrastructure-related courses, making it difficult for students to acquire these skills. This paper outlines how and why we are training students in HPC systems engineering, including the technologies used in delivering this goal. We demonstrate the potential for a multi-tenant HPC system for education and research, using novel container and cloud-based architecture. This work is supported by our previously published work that uses the latest open-source technologies to create sustainable, fast and flexible turn-key HPC environments with secure access via an HPC portal. The proposed multi-tenant HPC resources can be deployed on a “bare metal” infrastructure or in the cloud. An evaluation of our activities over the last five years is given in terms of recruitment metrics, skills audit feedback from students, and research outputs enabled by the multi-tenant usage of the resource.

scholarly journals Colorectal tumour simulation using agent based modelling and high performance computing

2017 ◽  
Vol 67 ◽  
pp. 397-408 ◽  
Author(s):  
Guiyeom Kang ◽  
Claudio Márquez ◽  
Ana Barat ◽  
Annette T. Byrne ◽  
Jochen H.M. Prehn ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Colorectal Tumour ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Performance Computing

scholarly journals Agent-based Robust Grid Scheduling Framework for High Performance Computing

2012 ◽  
Vol 1 ◽  
pp. 554-560 ◽  
Author(s):  
Syed Nasir Mehmood Shah ◽  
Nazleeni Haron ◽  
M Nordin B. Zakaria ◽  
Ahmad Kamil Bin Mahmood
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Grid Scheduling ◽  
Agent Based ◽  
Performance Computing
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