Evan F. Bollig

Solution to PDEs using radial basis function finite-differences (RBF-FD) on multiple GPUs

This paper presents parallelization strategies for the radial basis function-finite difference (RBF-FD) method. As a generalized finite differencing scheme, the RBF-FD method functions without the need for underlying meshes to structure nodes. It offers high-order accuracy approximation and scales as O ( N ) per time step, with N being with the total number of nodes. To our knowledge, this is the first implementation of the RBF-FD method to leverage GPU accelerators for the solution of PDEs. Additionally, this implementation is the first to span both multiple CPUs and multiple GPUs. OpenCL kernels target the GPUs and inter-processor communication and synchronization is managed by the Message Passing Interface (MPI). We verify our implementation of the RBF-FD method with two hyperbolic PDEs on the sphere, and demonstrate up to 9x speedup on a commodity GPU with unoptimized kernel implementations. On a high performance cluster, the method achieves up to 7x speedup for the maximum problem size of 27,556 nodes.

VLab: collaborative Grid services and portals to support computational material science

We present the initial architecture and implementation of VLab, a Grid and Web‐Service‐based system for enabling distributed and collaborative computational chemistry and material science applications for the study of planetary materials. The requirements of VLab include job preparation and submission, job monitoring, data storage and analysis, and distributed collaboration. These components are divided into client entry (input file creation, visualization of data, task requests) and back‐end services (storage, analysis, computation). Clients and services communicate through NaradaBrokering, a publish/subscribe Grid middleware system that identifies specific hardware information with topics rather than IP addresses. We describe three aspects of VLab in this paper: (1) managing user interfaces and input data with JavaBeans and Java Server Faces; (2) integrating Java Server Faces with the Java CoG Kit; and (3) designing a middleware framework that supports collaboration. To prototype our collaboration and visualization infrastructure, we have developed a service that transforms a scalar data set into its wavelet representation. General adaptors are placed between the endpoints and NaradaBrokering, which serve to isolate the clients/services from the middleware. This permits client and service development independently of potential changes to the middleware. Copyright

Acceleration of derivative calculations with application to radial basis function: finite-differences on the intel mic architecture

In this paper, we develop an efficient scheme for the cal- culation of derivatives within the context of Radial Ba- sis Function Finite-Difference (RBF-FD). RBF methods express functions as a linear combination of spherically symmetric basis functions on an arbitrary set of nodes. The Finite-Difference component expresses this combi- nation over a local set of nodes neighboring the point where the derivative is sought. The derivative at all points takes the form of a sparse matrix/vector multiplication (SpMV). In this paper, we consider the case of local stencils with a fixed number of nodes at each point and encode the sparse matrix in ELLPACK format. We increase the number of operations relative to memory bandwidth by interleaving the calculation of four derivatives of four different functions, or 16 different derivatives. We demonstrate a novel implementation on the Intel MIC archi- tecture, taking into account its advanced swizzling and channel interchange features. We present benchmarks on a real data set that show an almost sevenfold in- crease in speed compared to efficient implementations of a single derivative, reaching a performance of almost 140 Gflop/s in single precision. We explain the results through consideration of operation count versus memory bandwidth.

From Bare Metal to Virtual: Lessons Learned when a Supercomputing Institute Deploys its First Cloud

As primary provider for research computing services at the University of Minnesota, the Minnesota Supercomputing Institute (MSI) has long been responsible for serving the needs of a user-base numbering in the thousands. In recent years, MSI---like many other HPC centers---has observed a growing need for self-service, on-demand, data-intensive research, as well as the emergence of many new controlled-access datasets for research purposes. In light of this, MSI constructed a new on-premise cloud service, named Stratus, which is architected from the ground up to easily satisfy data-use agreements and fill four gaps left by traditional HPC. The resulting OpenStack cloud, constructed from HPC-specific compute nodes and backed by Ceph storage, is designed to fully comply with controls set forth by the NIH Genomic Data Sharing Policy. Herein, we present twelve lessons learned during the ambitious sprint to take Stratus from inception and into production in less than 18 months. Important, and often overlooked, components of this timeline included the development of new leadership roles, staff and user training, and user support documentation. Along the way, the lessons learned extended well beyond the technical challenges often associated with acquiring, configuring, and maintaining large-scale systems.

Toolkits for automatic web service and GUI generation

In a previous paper, we explained how to translate an input script into a functional web service, independent of the script language. We extend this work by considering the automatic creation of graphical user interfaces to allow interaction between a user and the web service generated by KWATT. The key aspects of this work are three‐fold. First, comment lines inserted into the script provide hints to the interface generator regarding the interface widgets. Second, the structure of the GUI is encoded into an XML file, and third, a plugin architecture permits the interface to be the output in one of several languages. We present an example interface to illustrate the concepts. Copyright