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Explore our

digital assets

Introduction

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The Innovation Return on Research (IROR) programme is a 5 year collaboration between the Hartree Centre and IBM Research, which aims to solve industry challenges and create economic and societal impact. We are developing a suite of digital assets which are industry relevant in the areas of Chemistry & Materials, Life Sciences and Engineering & Manufacturing. Businesses from these sectors have engaged with the programme as partners through projects which validate and shape the capabilities of our digital assets. Underpinning IROR is a cross-cutting Enabling Technologies programme, applicable to a wide range of industries.

IROR digital assets consist of reusable software components or workflows that have been designed and validated through challenge-led projects with partner companies in the IROR programme. They have been designed so that businesses can use them for similar applications but they are also flexible enough so they can be adapted or recombined to address new challenges in the future.

Our digital assets are now available for companies to access through various adoption routes including Platform as a Service, software licensing or collaborative R&D projects. Please do explore their capabilities, applications and potential benefits for your business.

Alison Kennedy Director | STFC Hartree Centre

Adoption routes

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Platform as a Service (PaaS) Software licensing Collaborative R&D projects

We offer a range of high performance

computing (HPC), artificial intelligence

(AI), data analytics and visual computing

resources to customers on a pre-paid, or

pay as you go basis.

Customers may supply their own simulation

software to use on our platforms, or may

opt to use Hartree Centre digital assets for a

premium on top of standard compute time

and storage costs.

Platform as a Service (PaaS) projects can

also include support from Hartree Centre

staff, at an additional cost.

Many of our digital assets are available for

organisations to access and use under commercial

license terms.

Upon payment of a license fee, access will be

given to the source code of the digital asset,

typically for a period of one year.

Additional license terms can be negotiated on

a case-by-case basis. Organisations can deploy

digital assets on their own on premise or cloud

computing resources.

3-month, no-cost evaluation licenses are also

available.

Examples of collaborative R&D projects

could involve the set up or running of

simulations to answer specific industrial

challenges defined by the customer.

An R&D project could also be used

to complete the necessary software

development as a step towards eventual

software licensing or PaaS.

Projects are costed at Full Economic

Costs, and may be paid for by the client

or (part) grant-funded through a range of

programmes.

Best for: Organisations who want to access

our state of the art HPC platforms quickly,

reducing costs and accelerating product

development.

Best for: This adoption route is well suited to

organisations with in-house software development

and compute resources or data that cannot leave

their premises.

Best for: Organisations who want to

use our digital assets but do not have

the capability or capacity available in

house. We can also modify a digital

asset to make it suitable for your specific

requirements.

Chemistry & Materials

For businesses to remain competitive they must move away from ad-hoc, labour intensive and expensive approaches towards a more robust and adaptive computer-aided paradigm.

Our Chemistry and Materials programme brings together STFC’s expertise in atomistic and mesoscale modelling with IBM’s artificial intelligence (AI) technologies to transform chemical and materials product design. This will boost efficiency in development of new products, especially for high value manufacturing supply chains.

Our digital assets will:

• Reduce time to market

• Provide an adaptive response to supply chain variability

• Enable development for sustainability

• Accelerate R&D processes

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• Cost reduction and reduced time to market by replacing physical experiments with simulation

• New insights into product performance

Particle Dynamics ModellerSimulation tools for Dissipative Particle Dynamics

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Dissipative Particle Dynamics (DPD) is a meso-scale simulation method, suitable for modelling a wide range of industry products. We have developed a suite of interoperable tools for DPD simulations spanning the whole modelling workflow from system setup, to running simulations on GPU-accelerated high performance computing platforms alongside statistical and graphical analysis of simulation results.

Our tools are available for organisations to access under a commercial license for use on your own platforms, or through our Platform as a Service (PaaS) offering. We can also support bespoke simulation projects through collaborative R&D.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

Yes Yes Yes

Applications

Suitable for modelling a wide range of industry products including:

• Personal and home care products; creams and gels

• Lubricants

• Fuels incl. additives

• Polymer melts and waxes

• Cost reduction through improved simulation accuracy

Parameterisation EngineAutomated model creation

Benefits

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Applications

Suitable for parameterising a wide range of industry products including:

• Personal and home care products; creams and gels

• Lubricants

• Fuels incl. additives

• Polymer melts and waxes

For robust modelling and accurate results – we need high quality models, however parameterising even simple models like Dissipative Particle Dynamics (DPD) is a difficult and time consuming task that must be done at the outset of any simulation project.

We have a developed a range of tools and approaches for generating industry-quality bespoke parameter sets for DPD simulations. These can be based on experimental data or on first principle calculations using Density Functional Theory. Parameter sets can be optimised using either a Force-balance method, or Bayesian optimisation.

Our MEAMfit tool is available for organisations under a commercial license. Use of the entire tool set is available through our Platform as a Service offering. We can also generate bespoke parameter sets for your organisation as part of a collaborative R&D project.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

Yes (MEAMfit) Yes Yes

• Accessible through an easy to use iPad interface

• Experiments can be run remotely

• User friendly

• Saves staff time learning to use HPC and simulation tools

Consumable Computing for ChemistryMaking simulation accessible to all

Benefits

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Building on the Particle Dynamics Modeller, we have developed a series of virtual experiments that are digital analogues of lab-based formulation chemistry. R&D scientists in your organisation can both configure experiments and execute them remotely on our high performance computing (HPC) platforms at the Hartree Centre.

Examples of virtual experiments

• Salt curve plotting

• Meso-structure mapping

• Micelle formation

• Adsorption isotherms of surfactants on

to surfaces

• Phase boundary detection (ternary phase

diagrams)

• Isothermal compressibility experiments

• Rheology of surfactants in microfluidic

channels

This provides a Simulation as a Service (SaaS) interface to our systems. Customisation for your organisation or implementation of new virtual experiments can be delivered as collaborative R&D projects.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

No Yes Yes

Applications

• Replacing laboratory formulation chemistry experiments with computer simulation

• Improved accuracy

• Fewer simulations required

• Cost-saving

• Faster

AI Accelerator for Chemistry Compute smarter

Benefits

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Parameter sweep-type operations such as phase diagram exploration can be accelerated by adopting an artificial intelligence (AI) approach, learning the shape of the parameter space in real-time within the program.

Bayesian Optimisation automatically balances refining the detail of interesting features (exploitation) with ensuring good coverage of the whole space (exploration), using far fewer simulations than a grid-based approach. In the end, a more accurate result is achieved more quickly, and for lower cost.

The Artificial Intelligence (AI) accelerator forms part of some of the virtual experiments available through the Consumable Computing for Chemistry interface. This approach could be adapted to your organisation as part of a collaborative R&D project.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

No Yes Yes

Applications

• Accelerating phase-diagram exploration experiments

Engineering & Manufacturing

We are developing software tools and methods for high fidelity modelling, uncertainty quantification, code coupling, simulation and optimisation to create virtual products.

Our digital assets will:

• Reduce development costs

• Improve product performance

• Reduce time to market

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• Flexible and scalable approach to code-coupling

• Cost reduction and reduced time to market, by replacing physical experiments with simulation

• New insights into product performance

Multiphysics and Multiphase Code Coupler Scalable and flexible code coupling

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Industry-relevant systems often require a modelling approach which spans multiple scales (e.g. atomistic and macroscopic) or physical models (e.g. CFD and solid mechanics) to capture all the relevant behaviour of a virtual product. This requires coupling together two or more models, often implemented in separate simulation codes. We have developed the open-source Multiscale Universal Interface (MUI) library with inter-process communication, spatial and temporal data samplers, and a Python API to approach this. Alongside the MUI library, we also have a set of adaptors that couple specific simulation codes:

CFD Thermal transfer Reactor dynamics Particle transport

Code_Saturne

OpenFOAM

SYRTHES DYN3D OpenMC

The core MUI library is available under Apache or GPL open-source licenses. If your organisation is interested in coupling any of the codes listed, a commercial license from STFC is available. MUI can also be accessed as part of our Platform as a Service (PaaS) offering. Support on bespoke code coupling applications is available through a collaborative R&D project.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

Yes Yes Yes

Applications

Modelling industrial processes and products including:

• Aerospace & automotive

• Compressors & turbines

• Marine/submarine

• Nuclear

• Industrial plants

• Better understanding of performance variation

• Discovery of rare product failure modes

• Cost reduction by reducing the number of simulations required

Quantification of Uncertainty Toolkit

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For many engineering applications, simple, fast and cheap simulation methods can reproduce the results of a more accurate and more computationally demanding model to within a defined tolerance level. To make virtual product design a reality, we must be able to quantify and control the size of the errors made by the model, understanding the sensitivity outputs to the values of input parameters.

Our QUTE toolkit can build ‘surrogate models’ – simpler, cheaper and faster methods capable of reproducing results of more accurate and computationally demanding models to within a defined tolerance level. It automates the process of parametric uncertainty studies, including selection of parameters to sample (using methods such as Polynomial Chaos and multi-level Monte Carlo), submission of simulation tasks to computing platforms, retrieval and analysis of results. QUTE is available under a commercial software license, or can be deployed on our high performance computing (HPC) resources via our Platform as a Service offering. Customisation of QUTE to support specific HPC systems can be carried out through collaborative R&D projects.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

Yes Yes Yes

Applications

• Virtual product design and optimisation

• Modelling the operation of industrial processes

for Engineering (QUTE)Computing the unknown

Using Hartree Centre skills and software can:

• Reduce costs

• Reduce time to market

Simulation Methods for

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Building on our code coupling and artificial intelligence (AI) tools and expertise, we have developed simulation models for a wide range of applications.

Applications of our simulation models

• Acoustic performance prediction and

optimisation of axial compressors

• Multiphase flow jet break-up for

industrial mixing

• Fluid-structure interactions

• Carbon deposition modelling on nuclear

fuel pins

• Transient thermal flows in complex pipe

geometries

• Neutronics and convection for reactor

modelling

• Ice accretion on aircraft wings

We provide a collaborative R&D service to build bespoke simulation models, either for deployment on our high performance computing (HPC) platforms or for HPC resources within your organisation.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

No No Yes

Applications

Modelling industrial processes and products including:

• Aerospace & automotive

• Compressors & turbines

• Marine/submarine

• Nuclear

• Industrial plants

Engineering ApplicationsBuilding the virtual product

• Knowledge capture by training AI using expert input

• Improved efficiency of existing capital infrastructure

AI-driven Process Simulation Using AI to control systems

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Industrial processes from waste water treatment to factory packing lines, are controlled by manual or semi-automated rule-based approaches. Machine learning offers the opportunity to build control systems which can adapt to changing conditions and optimise themselves to meet business requirements – for example reducing energy use, cost, or improving output quality.

By building simulation models, or by learning how a process behaves from operational data, we can provide recommendations as to how process operations can be improved. Contact us to discuss collaborative R&D projects to model and improve your business processes.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

No No Yes

Applications

Optimisation and control of industrial processes including:

• Production and packing lines

• Water treatment and distribution

Life sciences

Advances in molecular simulation and high-throughput sequencing have created a deluge of biological data. We are using this to develop new data-driven approaches to molecular design and metagenomics analysis.

Our digital assets will:

Combine method development with practical implementation of existing technology to build cutting-edge applications in:• Data driven

antimicrobial peptide design

• Soil and crop metagenomics

• Precision agriculture

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• Improved product efficacy by rapid, large-scale screening

• Cost reduction by reducing number of lab experiments required

Virtual Membrane Binding and

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Rapid screening of candidate drug compounds remains a major challenge for the pharmaceutical industry. Accurate approaches that accelerate the discovery process and provide new insights at a molecular scale can increase the number of lead compounds that can be screened, reducing costs by focusing lab testing on peptides with a high chance of success.

Our virtual assay rapidly screens potential anti-microbial peptides by computing free energies of binding and insertion into biological membranes in parallel using a HPC workflow. We then adopt a data-centric approach to identify novel peptide sequences which have anti-microbial properties but are harmless to human cells. This method has allowed us to discover new compounds and verify effectiveness in the lab.

You can access the virtual assay on our high performance computing systems via Platform as a Service (PaaS). Customising the workflow for new classes of applications or for activity against a different biological target could be approached through a collaborative R&D project.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

No Yes Yes

Applications

Screening and designing anti-microbial and anti-fungal agents including:

• Small molecule drugs

• Linear and cyclic peptides

Permeation AssayVirtual screening for anti-microbial peptides

• Reduced costs by using more efficient algorithms

• Data compression

• New applications enabled through real-time analysis

Omics Analytics Toolkit Extracting knowledge from omics data

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Applications

Analysis of metagenomic data including:

• Skin and mouth microbiome

• Gut / faecal microbiome

• Soil microbiome

• Gene profiling

We are developing tools which can be used to build powerful and efficient analytics pipelines for metagenomic data. The Microbiome Characterisation Utilities (MCU) are based on our novel methods for metagenome analysis.

Microbiome Characterisation Utilities (MCU)

graphMap histoSketch sketchPredict geneFlow

Combining variation

graph respresentation of

gene sets with a locality-

sensitive hashing indexing

scheme, graphMap can

perform accurate gene

profiling of microbiome

samples in minutes using

just a laptop.

Using similarity-preserving

sketches to represent

streaming k-mer spectra,

histoSketch can compress

large microbiome samples

to small sketches. These

can be indexed, searched

or classified in real-time.

Applying machine

learning classifiers

to sketches,

sketchPredict is able

to classify microbiome

samples according to

phenotype or other

metadata.

Combining MCU

components with the

powerful Nextflow

framework, geneFlow is

able to identify microbiome

samples of interest, perform

gene and taxonomic

profiling and predict gene

context.

These tools are available to companies under a commercial license. We can develop bespoke analytics pipelines for specific applications via collaborative R&D projects.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

Yes No Yes

Enabling technologies

Underpinning Innovation Return on Research (IROR) is a technology development programme, delivering cutting edge machine learning at scale, exploring new data technologies and a platform to allow industry collaborators to exploit our digital assets in their organisation.

Our digital assets will:

• Reduce costs by accelerating the time taken to reach a solution

• Highlight new applications through large-scale data analytics

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• Portability of code on current and future architectures

• Reduced costs

• Faster time to simulation

Code analysis and generation for HPC Automating performance optimisation

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As next generation architectures continue to evolve, increasing performance, it is important to adapt software to realise gains in speed. We have developed a suite of tools that can analyse source code and generate auto-tuned kernels for emerging architectures. These have been used as part of the PSyclone project to generate code for the Met Office’s next generation weather forecast model.

Code analysis and code generation tools for HPC

• PSyclone: code generation for weather

modelling

• Fparser: a Fortran code parser

• Fgenerator: a Fortran code generator

• Melody: automated performance

tuning

• Habakkuk: performance prediction

from Fortran source code

The tools above are available under open source licenses, free of charge. Hartree Centre also provide bespoke software profiling, analysis and optimisation services.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

No No Yes

Applications

High performance computing (HPC) optimisation of simulation codes:

• Weather & climate modelling

• Computational Fluid Dynamics (CFD)

• Materials modelling

• Increased efficiency of product operation and production

• Reduced training time for image classification tasks

Machine Learning at Scale More than Deep Neural Networks

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Applications

General purpose optimisation problems including:

• Product design

• Process optimisation

• Drug design

• Deep neural network training

We have developed a range of advanced machine learning capabilities, covering two classes of application:

Machine learning at scale applications

Bayesian Optimisation Image detection and classification

A flexible and efficient method for global optimisation

that is able to balance between exploration and

exploitation: when to prioritise between learning

about the unknown and when to improve on the best

known solution. We have applied this approach in

a range of areas from optimisation of aerodynamic

wings to designing small molecule drugs for biomedical

applications.

Building and tuning deep neural networks for specific

applications such as object detection and labelling.

Using our IBM Power systems with NVIDIA GPUs, we

can train complex neural networks much more rapidly

than conventional compute resources.

Our Bayesian Optimisation tools are accessible through

an API - Bayesian Optimisation as a Service (BOaaS),

allowing end users to build their own applications

without having to deploy the tools on premises.

Our team are able to develop image processing

models for specific applications through collaborative

R&D projects.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

No Yes Yes

• Cost saving by automation of data ingestion, alignment and analysis

• New applications enabled by very large scale data analytics

Data Technology Platform Enabling big data applications

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Based on IBM PAIRS technology, we have the ability to handle very large geospatial data sets and use them to build bespoke applications, for example crop pest prediction for precision agriculture.

To explore how this technology could be used for your application, contact us for access to the platform or to discuss potential collaborative R&D projects.

Adoption routes

Software Licensing PaaS/SaaS Collaborative R&D

No No Yes

Applications

Geospatial data applications including:

• Agritech

• Logistics

• Weather

• Routing

www.hartree.stfc.ac.uk

@hartreecentre /company/stfc-hartree-centre hartree@stfc.ac.uk®

The Hartree Centre was created to transform UK industry by accelerating the adoption of high performance computing (HPC), big data analytics and artificial intelligence (AI) technologies. We play a key role in realising the UK Government Industrial Strategy by stimulating applied digital research and innovation, creating value for the organisations we work with and generating economic and societal impact for the UK.

The Science and Technology Facilities Council (STFC) Hartree Centre is part of UK Research and Innovation.