Dr Kevin Berwick
High Performance Computing
High-performance computing (HPC) evolved due to meet increasing demands for processing speed. HPC brings together hardware and software to solve advanced problems effectively. HPC focuses on developing parallel processing algorithms to divide big problems into small pieces. Each piece is solved on a separate processor and then the results are combined.
The first language I learned was PASCAL as an undergraduate. Since then I have toyed with MATLAB, Python, Julia and a little Assembly. If you are a student who would like to do some work with me, you can use any language you like, on Linux or Windows, it is entirely up to you.
My current interests in HPC include the numerical simulation of quantum confinement, soliton behaviour, earthquake modelling, neural networks, shockwaves, fluid dynamics, CUDA, HPC in the Cloud, the Fermi Pasta Ulam Problem, protein folding, the Ising model of magnetism, molecular dynamics and ballistics.
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If you are interested in any of these problems, HPC, Scientific Computing, or just want a chat about Projects, take a look at the Sample Reports sections of this website to learn more.
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Then get in touch with me! I’m looking forward to hearing from you........
HPC hardware platforms available in the School of Electrical and Electronic Engineering
SEEE High Performance Computing Blade
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This is a Dell PowerEdge R730 Blade. This machine is used for a wide variety of research activities in the School. I have run a number of Projects on this system in the area of Protein Folding, Mathematics, Heat flow, Orbital simulation, Quantum mechanics, Climate modelling and Molecular Dynamics. Access is via your desktop and a Virtual Machine.
The system is managed by Mr. Andrew Dillon, above right, HPC System Administrator. You can email him at andrew.dillon@tudublin.ie with queries or to apply for an Account.
Irish Centre for High End Computing (ICHEC)
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This is a National facility. Kay is comprised of a number of components:
"Cluster" - A cluster of 336 nodes where each node has 2x 20-core 2.4 GHz Intel Xeon Gold 6148 (Skylake) processors, 192 GiB of RAM, a 400 GiB local SSD for scratch space and a 100Gbit OmniPath network adaptor. This partition has a total of 13,440 cores and 63 TiB of distributed memory.
"GPU" - A partition of 16 nodes with the same specification as above, plus 2x NVIDIA Tesla V100 16GB PCIe (Volta architecture) GPUs on each node. Each GPU has 5,120 CUDA cores and 640 Tensor Cores.
"Phi" - A partition of 16 nodes, each containing 1x self-hosted Intel Xeon Phi Processor 7210 (Knights Landing or KNL architecture) with 64 cores @ 1.3 GHz, 192 GiB RAM and a 400 GiB local SSD for scratch space.
"High Memory" - A set of 6 nodes each containing 1.5 TiB of RAM, 2x 20-core 2.4 GHz Intel Xeon Gold 6148 (Skylake) processors and 1 TiB of dedicated local SSD for scratch storage.
"Service & Storage" - A set of service and administrative nodes to provide user login, batch scheduling, management, networking, etc. Storage is provided via Lustre filesystems on a high-performance DDN SFA14k system with 1 PiB of capacity.
A number of my students have successfully applied for time on ICHEC facilities.
Scientific Computing
If you are interested in Computational Physics, take a look at the book, Computational Physics, by Nicholas Giordano and Hisao Nakanishi, available in the library in Grangegorman. I have writtten a FREE Book, Computational Physics with MATLAB®, to accompany this book. Below is some eye candy from the book!
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Student Projects
Here are some examples of my student's work. Hopefully your work will appear here soon. If any of the pictures you see here appeal or intrigue you, please get in touch to discuss projects..and check out the Sample Reports sections of this website for more!
