Introduction to HPC Systems

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Iridis 6: One of Southampton’s High Performance Computing clusters
Iridis 6: One of Southampton’s High Performance Computing clusters

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Your PC is your local computing resource, good for small computational tasks.

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Outsourcing Computational Tasks: many of the tasks we perform daily using computers are outsourced to remote servers
Outsourcing Computational Tasks: many of the tasks we perform daily using computers are outsourced to remote servers

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High Performance Computing System Architecture: Simplified schematic of an HPC cluster.
High Performance Computing System Architecture: Simplified schematic of an HPC cluster.

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High Performance Computing Landscape: In the UK HPC facilities are divided into tiers based upon their size.
High Performance Computing Landscape: In the UK HPC facilities are divided into tiers based upon their size.

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Accessing and Using HPC Resources

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Iridis On Demand: A web portal to the University of Southampton’s HPC Cluster, Iridis
Iridis On Demand: A web portal to the University of Southampton’s HPC Cluster, Iridis

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File Manager in Iridis On Demand: Moving data to and from the Iridis HPC system can be achieved in the Open On Demand Web Portal
File Manager in Iridis On Demand: Moving data to and from the Iridis HPC system can be achieved in the Open On Demand Web Portal

Introduction to Job Scheduling

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Queueing up to eat at a popular restaurant is like queueing up to run something on an HPC cluster.
Queueing up to eat at a popular restaurant is like queueing up to run something on an HPC cluster.

Introduction to Programmatic Parallelism

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On the left, a single processing unit executes one sequence of instructions for the whole problem. On the right, the problem is divided into independent tasks, each processed concurrently by separate processing units.
On the left, a single processing unit executes one sequence of instructions for the whole problem. On the right, the problem is divided into independent tasks, each processed concurrently by separate processing units.

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Multiple independent processes, each with their own private memory space, communicating through explicit message passing over a network.
Multiple independent processes, each with their own private memory space, communicating through explicit message passing over a network.

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Multiple threads within a single process, sharing the same memory space and resources.
Multiple threads within a single process, sharing the same memory space and resources.

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Comparison of shared and distributed memory architectures: shared memory shows multiple processors accessing one memory pool, while distributed memory shows processors each with private memory connected by communication links.
Comparison of shared and distributed memory architectures: shared memory shows multiple processors accessing one memory pool, while distributed memory shows processors each with private memory connected by communication links.

Landscape of HPC Technologies

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Measuring and improving parallel performance

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A plot showing the measured speed up against number of processors. In this example, we can see that our code scales very well up to 16 processors. However, beyond this amount the speed up starts to diverge from ideal scaling. Once we start using 128 processors we can see that it’s detrimental and the code performs worse!
A plot showing the measured speed up against number of processors. In this example, we can see that our code scales very well up to 16 processors. However, beyond this amount the speed up starts to diverge from ideal scaling. Once we start using 128 processors we can see that it’s detrimental and the code performs worse!

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A plot showing the measured efficiency against process count. We can see in this case that this code does not scale well at all in a weak scaling test.
A plot showing the measured efficiency against process count. We can see in this case that this code does not scale well at all in a weak scaling test.