Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Toward interoperable bioscience data

© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Genetics 44 (2012): 121-126, doi:10.1038/ng.1054.To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.The authors also acknowledge the following funding sources in particular: UK Biotechnology and Biological Sciences Research Council (BBSRC) BB/I000771/1 to S.-A.S. and A.T.; UK BBSRC BB/I025840/1 to S.-A.S.; UK BBSRC BB/I000917/1 to D.F.; EU CarcinoGENOMICS (PL037712) to J.K.; US National Institutes of Health (NIH) 1RC2CA148222-01 to W.H. and the HSCI; US MIRADA LTERS DEB-0717390 and Alfred P. Sloan Foundation (ICoMM) to L.A.-Z.; Swiss Federal Government through the Federal Office of Education and Science (FOES) to L.B. and I.X.; EU Innovative Medicines Initiative (IMI) Open PHACTS 115191 to C.T.E.; US Department of Energy (DOE) DE-AC02- 06CH11357 and Arthur P. Sloan Foundation (2011- 6-05) to J.G.; UK BBSRC SysMO-DB2 BB/I004637/1 and BBG0102181 to C.G.; UK BBSRC BB/I000933/1 to C.S. and J.L.G.; UK MRC UD99999906 to J.L.G.; US NIH R21 MH087336 (National Institute of Mental Health) and R00 GM079953 (National Institute of General Medical Science) to A.L.; NIH U54 HG006097 to J.C. and C.E.S.; Australian government through the National Collaborative Research Infrastructure Strategy (NCRIS); BIRN U24-RR025736 and BioScholar RO1-GM083871 to G.B. and the 2009 Super Science initiative to C.A.S

Pseudospectra of the Linear Navier-Stokes Evolution Operator and Instability of Plane Poiseuille and Couette Flows: (preliminary report)

This is a rough, interim report on some new results concerning the stability of plane Poiseuille and Couette fluid flows, following upon recent work by Henningson and Reddy, Butler and Farrell, Gustavsson and others. We emphasize that the conclusions proposed here have not yet been checked carefully and are subject to change. Our principal results are as follows: 1. Plots of the spectra of the "full" Navier-Stokes operator for Poiseuille and Couette flows, i.e., without restriction to a wave number pair ($\alpha, \beta$) or to even or odd modes ($\S\S$4,5). 2. Analogous plots for the pseudospectra of this operator. Comparison of the pseudospectra with the spectra gives a new interpretation of why the physics of these linear flow problems is not controlled by the location of the most unstable eigenvalue ($\S\S$4,5). 3. Demonstration that these pseudospectra predict the Butler-Farrell "optimal" transient energy growth ratios to within a factor of about 2 ($\S$6). 4. Demonstration that about 90% of the Butler-Farrell growth can be achieved by a 3$\times$3 linear model obtained by projecting the Navier-Stokes problem onto the space spanned by three dominant eigenmodes, for Couette flow, or four in the case of Poiseuille flow ($\S$8). 5. Demonstration that although 1 Orr-Sommerfeld mode and 3 Squire modes suffice for the 4$\times$4 model in the Poiseuille case, in keeping with a recent result of Gustavsson, one can do equally well with 2 modes of each kind or with 3 Orr-Sommerfeld modes and 1 Squire mode ($\S$8). 6. Demonstration that the minimal operator perturbation required to destabilize a stable flow has norm of order $R^-$$^2$, where $R$ is the Reynolds number, though the distance of the least stable eigenvalue from the real axis is $O (R^-$$^1$) ($\S$7). 7. Presentation of a 2$\times$2 model illustrating that if the linear problems described above are capable of transient energy growth of order $M$ (e.g., $M\approx$1000 according to Butler and Farrell), a weak and intrinsically energy-conserving nonlinear term can "bootstrap" that growth to a higher order such as $M^2$. This supports the view that although nonlinear terms are of course essential to the subcritical instability of fluid flows, the detailed nature of the nonlinear interactions may sometimes be relatively unimportant ($\S$2). 8. Adaptation of this "bootstrapping" idea to the fluid flows considered earlier, particularly the 3$\times$3 approximation for Couette flow with $R$=1000

MultiMATLAB: Integrating MATLAB with High-Performance Parallel Computing

Matlab is the most popular scientific computing environment available on uniprocessors today. Unfortunately, no such environment is currently available for multiprocessors. MultiMatlab [1] is a general extension of the Matlab environment to any distributed memory multiprocessors. This paper presents a new MultiMatlab system designed to provide high-performance on multiprocessors while maintaining the functionality and usability of the Matlab environment. This system will enable users to access high-performance parallel routines from within the Matlab environment, to extend the environment with new parallel routines, and to use these routines to develop parallel applications with the Matlab language. We discuss a general MultiMatlab architecture, present two implementations based upon the MPI communication standard [2], and demonstrate the use of this system. Preliminary results indicate that the MultiMatlab system can offer the full performance of the underlying multiprocessor to the ..

A New Direction in Hydrodynamic Stability: Beyond Eigenvalues

Fluid flows that are smooth at low speeds become unstable and then turbulent at higher speeds. This phenomenon has traditionally been investigated by linearizing the equations of flow and looking for unstable eigenvalues of the linearized problem, but the results agree poorly in many cases with experiments. Nevertheless, it has become clear in recent years that linear effects play a central role in hydrodynamic instability. A reconciliation of these findings with the traditional analysis can be obtained by considering the "pseudospectra" of the linearized problem, which reveal that small perturbations to the smooth flow in the form of streamwise vortices may be amplified by factors on the order of 10**5 by a linear mechanism, even though all the eigenmodes are stable. The same principles apply also to other problems in the mathematical sciences that involve non-orthogonal eigenfunctions