233 research outputs found
Predictive analysis of a hydrodynamics application on large-scale CMP clusters
We present the development of a predictive performance model for the high-performance computing code Hydra, a hydrodynamics benchmark developed and maintained by the United Kingdom Atomic Weapons Establishment (AWE). The developed model elucidates the parallel computation of Hydra, with which it is possible to predict its runtime and scaling performance on varying large-scale chip multiprocessor (CMP) clusters. A key feature of the model is its granularity; with the model we are able to separate the contributing costs, including computation, point-to-point communications, collectives, message buffering and message synchronisation. The predictions are validated on two contrasting large-scale HPC systems, an AMD Opteron/ InfiniBand cluster and an IBM BlueGene/P, both of which are located at the Lawrence Livermore National Laboratory (LLNL) in the US. We validate the model on up to 2,048 cores, where it achieves a > 85% accuracy in weak-scaling studies. We also demonstrate use of the model in exposing the increasing costs of collectives for this application, and also the influence of node density on network accesses, therefore highlighting the impact of machine choice when running this hydrodynamics application at scale
Optimisation of patch distribution strategies for AMR applications
As core counts increase in the world's most powerful supercomputers, applications are becoming limited not only by computational power, but also by data availability. In the race to exascale, efficient and effective communication policies are key to achieving optimal application performance. Applications using adaptive mesh refinement (AMR) trade off communication for computational load balancing, to enable the focused computation of specific areas of interest. This class of application is particularly susceptible to the communication performance of the underlying architectures, and are inherently difficult to scale efficiently. In this paper we present a study of the effect of patch distribution strategies on the scalability of an AMR code. We demonstrate the significance of patch placement on communication overheads, and by balancing the computation and communication costs of patches, we develop a scheme to optimise performance of a specific, industry-strength, benchmark application
Helium nanodroplet isolation ro-vibrational spectroscopy: methods and recent results
In this article, recent developments in HElium NanoDroplet Isolation (HENDI)
spectroscopy are reviewed, with an emphasis on the infrared region of the
spectrum. Topics discussed include experimental details, comparison of
radiation sources, symmetry issues of the helium solvation structure, sources
of line broadening, changes in spectroscopic constants upon solvation, and
applications including formation of novel chemical structures.Comment: 24 pages, 8 figures, 3 tables; to be published in the Journal of
Chemical Physic
No wisdom in the crowd: genome annotation at the time of big data - current status and future prospects
Science and engineering rely on the accumulation
and dissemination of knowledge to make discoveries
and create new designs. Discovery-driven genome
research rests on knowledge passed on via gene
annotations. In response to the deluge of sequencing
big data, standard annotation practice employs automated
procedures that rely on majority rules. We
argue this hinders progress through the generation
and propagation of errors, leading investigators into
blind alleys. More subtly, this inductive process discourages
the discovery of novelty, which remains
essential in biological research and reflects the nature
of biology itself. Annotation systems, rather than
being repositories of facts, should be tools that support
multiple modes of inference. By combining
deduction, induction and abduction, investigators can
generate hypotheses when accurate knowledge is
extracted from model databases. A key stance is to
depart from āthe sequence tells the structure tells the
functionā fallacy, placing function first. We illustrate
our approach with examples of critical or unexpected
pathways, using MicroScope to demonstrate how
tools can be implemented following the principles we
advocate. We end with a challenge to the reader
The 8th International Conference on Time Series and Forecasting
The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation and use of new knowledge, computational techniques and methods on forecasting in a wide range of fields
Analytical modelling for the performance prediction and optimisation of near-neighbour structured grid hydrodynamics
The advent of modern High Performance Computing (HPC) has facilitated the use of powerful supercomputing machines that have become the backbone of data analysis and simulation. With such a variety of software and hardware available today, understanding how well such machines can perform is key for both efficient use and future planning. With significant costs and multi-year turn-around times, procurement of a new HPC architecture can be a significant undertaking.
In this work, we introduce one such measure to capture the performance of such machines ā analytical performance models. These models provide a mathematical representation of the behaviour of an application in the context of how its various components perform for an architecture. By parameterising its workload in such a way that the time taken to compute can be described in relation to one or more benchmarkable statistics, this allows for a reusable representation of an application that can be applied to multiple architectures.
This work goes on to introduce one such benchmark of interest, Hydra. Hydra is a benchmark 3D Eulerian structured mesh hydrocode implemented in Fortran, with which the explosive compression of materials, shock waves, and the behaviour of materials at the interface between components can be investigated. We assess its scaling behaviour and use this knowledge to construct a performance model that accurately predicts the runtime to within 15% across three separate machines, each with its own distinct characteristics. Further, this work goes on to explore various optimisation techniques, some of which see a marked speedup in the overall walltime of the application. Finally, another software application of interest with similar behaviour patterns, PETSc, is examined to demonstrate how different applications can exhibit similar modellable patterns
Virtual metrology for plasma etch processes.
Plasma processes can present dicult control challenges due to time-varying dynamics
and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the
use of mathematical models with accessible measurements from an operating process to
estimate variables of interest. This thesis addresses the challenge of virtual metrology
for plasma processes, with a particular focus on semiconductor plasma etch.
Introductory material covering the essentials of plasma physics, plasma etching, plasma
measurement techniques, and black-box modelling techniques is rst presented for readers
not familiar with these subjects. A comprehensive literature review is then completed
to detail the state of the art in modelling and VM research for plasma etch processes.
To demonstrate the versatility of VM, a temperature monitoring system utilising a
state-space model and Luenberger observer is designed for the variable specic impulse
magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The
temperature monitoring system uses optical emission spectroscopy (OES) measurements
from the VASIMR engine plasma to correct temperature estimates in the presence of
modelling error and inaccurate initial conditions. Temperature estimates within 2% of
the real values are achieved using this scheme.
An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate
plasma etch rate for an industrial plasma etch process is presented. The VM
models estimate etch rate using measurements from the processing tool and a plasma
impedance monitor (PIM). A selection of modelling techniques are considered for VM
modelling, and Gaussian process regression (GPR) is applied for the rst time for VM
of plasma etch rate. Models with global and local scope are compared, and modelling
schemes that attempt to cater for the etch process dynamics are proposed. GPR-based
windowed models produce the most accurate estimates, achieving mean absolute percentage
errors (MAPEs) of approximately 1:15%. The consistency of the results presented
suggests that this level of accuracy represents the best accuracy achievable for
the plasma etch system at the current frequency of metrology.
Finally, a real-time VM and model predictive control (MPC) scheme for control of
plasma electron density in an industrial etch chamber is designed and tested. The VM
scheme uses PIM measurements to estimate electron density in real time. A predictive
functional control (PFC) scheme is implemented to cater for a time delay in the VM
system. The controller achieves time constants of less than one second, no overshoot,
and excellent disturbance rejection properties. The PFC scheme is further expanded by
adapting the internal model in the controller in real time in response to changes in the
process operating point
Virtual metrology for plasma etch processes.
Plasma processes can present dicult control challenges due to time-varying dynamics
and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the
use of mathematical models with accessible measurements from an operating process to
estimate variables of interest. This thesis addresses the challenge of virtual metrology
for plasma processes, with a particular focus on semiconductor plasma etch.
Introductory material covering the essentials of plasma physics, plasma etching, plasma
measurement techniques, and black-box modelling techniques is rst presented for readers
not familiar with these subjects. A comprehensive literature review is then completed
to detail the state of the art in modelling and VM research for plasma etch processes.
To demonstrate the versatility of VM, a temperature monitoring system utilising a
state-space model and Luenberger observer is designed for the variable specic impulse
magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The
temperature monitoring system uses optical emission spectroscopy (OES) measurements
from the VASIMR engine plasma to correct temperature estimates in the presence of
modelling error and inaccurate initial conditions. Temperature estimates within 2% of
the real values are achieved using this scheme.
An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate
plasma etch rate for an industrial plasma etch process is presented. The VM
models estimate etch rate using measurements from the processing tool and a plasma
impedance monitor (PIM). A selection of modelling techniques are considered for VM
modelling, and Gaussian process regression (GPR) is applied for the rst time for VM
of plasma etch rate. Models with global and local scope are compared, and modelling
schemes that attempt to cater for the etch process dynamics are proposed. GPR-based
windowed models produce the most accurate estimates, achieving mean absolute percentage
errors (MAPEs) of approximately 1:15%. The consistency of the results presented
suggests that this level of accuracy represents the best accuracy achievable for
the plasma etch system at the current frequency of metrology.
Finally, a real-time VM and model predictive control (MPC) scheme for control of
plasma electron density in an industrial etch chamber is designed and tested. The VM
scheme uses PIM measurements to estimate electron density in real time. A predictive
functional control (PFC) scheme is implemented to cater for a time delay in the VM
system. The controller achieves time constants of less than one second, no overshoot,
and excellent disturbance rejection properties. The PFC scheme is further expanded by
adapting the internal model in the controller in real time in response to changes in the
process operating point
The readying of applications for heterogeneous computing
High performance computing is approaching a potentially significant change in architectural design. With pressures on the cost and sheer amount of power, additional architectural features are emerging which require a re-think to the programming models deployed over the last two decades.
Today's emerging high performance computing (HPC) systems are maximising performance per unit of power consumed resulting in the constituent parts of the system to be made up of a range of different specialised building blocks, each with their own purpose. This heterogeneity is not just limited to the hardware components but also in the mechanisms that exploit the hardware components. These multiple levels of parallelism, instruction sets and memory hierarchies, result in truly heterogeneous computing in all aspects of the global system.
These emerging architectural solutions will require the software to exploit tremendous amounts of on-node parallelism and indeed programming models to address this are emerging. In theory, the application developer can design new software using these models to exploit emerging low power architectures. However, in practice, real industrial scale applications last the lifetimes of many architectural generations and therefore require a migration path to these next generation supercomputing platforms.
Identifying that migration path is non-trivial: With applications spanning many decades, consisting of many millions of lines of code and multiple scientific algorithms, any changes to the programming model will be extensive and invasive and may turn out to be the incorrect model for the application in question.
This makes exploration of these emerging architectures and programming models using the applications themselves problematic. Additionally, the source code of many industrial applications is not available either due to commercial or security sensitivity constraints.
This thesis highlights this problem by assessing current and emerging hard- ware with an industrial strength code, and demonstrating those issues described. In turn it looks at the methodology of using proxy applications in place of real industry applications, to assess their suitability on the next generation of low power HPC offerings. It shows there are significant benefits to be realised in using proxy applications, in that fundamental issues inhibiting exploration of a particular architecture are easier to identify and hence address.
Evaluations of the maturity and performance portability are explored for a number of alternative programming methodologies, on a number of architectures and highlighting the broader adoption of these proxy applications, both within the authors own organisation, and across the industry as a whole
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