Wolfgang Frings

A new approach to measure single-event related brain activity using real-time fMRI: Feasibility of sensory, motor, and higher cognitive tasks

Real‐time fMRI is a rapidly emerging methodology that enables monitoring changes in brain activity during an ongoing experiment. In this article we demonstrate the feasibility of performing single‐event sensory, motor, and higher cognitive tasks in real‐time on a clinical whole‐body scanner. This approach requires sensitivity optimized fMRI methods: Using statistical parametric mapping we quantified the spatial extent of BOLD contrast signal changes as a function of voxel size and demonstrate that sacrificing spatial resolution and readout bandwidth improves the detection of signal changes in real time. Further increases in BOLD contrast sensitivity were obtained by using real‐time multi‐echo EPI. Real‐time image analysis was performed using our previously described Functional Imaging in REal time (FIRE) software package, which features real‐time motion compensation, sliding window correlation analysis, and automatic reference vector optimization. This new fMRI methodology was validated using single‐block design paradigms of standard visual, motor, and auditory tasks. Further, we demonstrate the sensitivity of this method for online detection of higher cognitive functions during a language task using single‐block design paradigms. Finally, we used single‐event fMRI to characterize the variability of the hemodynamic impulse response in primary and supplementary motor cortex in consecutive trials using single movements. Real‐time fMRI can improve reliability of clinical and research studies and offers new opportunities for studying higher cognitive functions. Hum. Brain Mapping 12:25–41, 2001.

Scalable massively parallel I/O to task-local files

Parallel applications often store data in multiple task-local files, for example, to remember checkpoints, to circumvent memory limitations, or to record performance data. When operating at very large processor configurations, such applications often experience scalability limitations when the simultaneous creation of thousands of files causes metadataserver contention or simply when large file counts complicate file management or operations on those files even destabilize the file system. SIONlib is a parallel I/O library that addresses this problem by transparently mapping a large number of task-local files onto a small number of physical files via internal metadata handling and block alignment to ensure high performance. While requiring only minimal source code changes, SIONlib significantly reduces file creation overhead and simplifies file handling without penalizing read and write performance. We evaluate SIONlibs efficiency with up to 288 K tasks and report significant performance improvements in two application scenarios.

Automatic Trace-Based Performance Analysis of Metacomputing Applications

The processing power and memory capacity of independent and heterogeneous parallel machines can be combined to form a single parallel system that is more powerful than any of its constituents. However, achieving satisfactory application performance on such a metacomputer is hard because the high latency of inter-machine communication as well as differences in hardware of constituent machines may introduce various types of wait states. In our earlier work, we have demonstrated that automatic pattern search in event traces can identify the sources of wait states in parallel applications running on a single computer. In this article, we describe how this approach can be extended to metacomputing environments with special emphasis on performance problems related to inter-machine communication. In addition, we demonstrate the benefits of our solution using a real-world multi-physics application.

Steering UNICORE applications with VISIT

The UNICORE (UNiform Interface to COmputing REsources) software provides a Grid infrastructure together with a computing portal for engineers and scientists to access supercomputer centres from anywhere on the Internet. While UNICORE is primarily designed for the submission and control of batch jobs, it is also feasible to establish an on-line connection between an application and the UNICORE user-client. This opens up the possibility of performing on-line visualization and computational steering of applications under UNICORE control while maintaining the security provided by this system. This contribution describes the design of a steering extension to UNICORE based on the steering toolkit VISIT (VISualization Interface Toolkit). VISIT is a lightweight library that supports bidirectional data exchange between visualizations and parallel applications. As an example application, a parallel simulation of a laser-plasma interaction that can be steered by an AVS/Express application is presented.

Progress in Mesh-Free Plasma Simulation With Parallel Tree Codes

The recent developments in mesh-free plasma modeling using parallel tree codes are described, covering the algorithmic and performance issues and how to apply this technique to multidimensional electrostatic plasma problems. Examples of the simulations of the ion acceleration by high-intensity lasers, heating, and the dynamics of the nanostructured targets, as well as more recent applications of this technique to the simulations of edge plasmas in tokamaks and mesh-free magnetoinductive models, are given.

Measuring power consumption on IBM Blue Gene/P

Energy efficiency is a key design principle of the IBM Blue Gene series of supercomputers, and Blue Gene systems have consistently gained top GFlops/Watt rankings on the Green500 list. The Blue Gene hardware and management software provide built-in features to monitor power consumption at all levels of the machine’s power distribution network. This paper presents the Blue Gene/P power measurement infrastructure and discusses the operational aspects of using this infrastructure on Petascale machines. We also describe the integration of Blue Gene power monitoring capabilities into system-level tools like LLview, and highlight some results of analyzing the production workload at Research Center Jülich (FZJ).

Recent Developments in the Scalasca Toolset

The number of processor cores on modern supercomputers is increasing from generation to generation, and as a consequence HPC applications are required to harness much higher degrees of parallelism to satisfy their growing demand for computing power. However, writing code that runs efficiently on large processor configurations remains a significant challenge. The situation is exacerbated by the rising number of cores imposing scalability demands not only on applications but also on the software tools needed for their development.

Massively parallel loading

Dynamic linking has many advantages for managing large code bases, but dynamically linked applications have not typically scaled well on high performance computing systems. Splitting a monolithic executable into many dynamic shared object (DSO) files decreases compile time for large codes, reduces runtime memory requirements by allowing modules to be loaded and unloaded as needed, and allows common DSOs to be shared among many executables. However, launching an executable that depends on many DSOs causes a flood of file system operations at program start-up, when each process in the parallel application loads its dependencies. At large scales, this operation has an effect similar to a site-wide denial-of-service attack, as even large parallel file systems struggle to service so many simultaneous requests. In this paper, we present SPINDLE, a novel approach to parallel loading that coordinates simultaneous file system operations with a scalable network of cache server processes. Our approach is transparent to user applications. We extend the GNU loader, which is used in Linux as well as proprietary operating systems, to limit the number of simultaneous file system operations, quickly loading DSOs without thrashing the file system. Our experiments show that our prototype implementation has a low overhead and increases the scalability of Pynamic, a benchmark that stresses the dynamic loader, by a factor of 20.

Design and evaluation of a collaborative online visualization and steering framework implementation for computational grids

Todays large-scale scientific research often relies on the collaborative use of a Grid or c-Science infrastructure (e.g. DEISA, EGEE, TeraGrid, OSG) with computational, storage, or other types of physical resources. One of the goals of these emerging infrastructures is to support the work of scientists with advanced problem-solving tools. Many e-Science applications within these infrastructures aim at simulations of a scientific problem on powerful parallel computing resources. Typically, a researcher first performs a simulation for some fixed amount of time and then analyses results in a separate post-processing step, for instance, by viewing results in visualizations. In earlier work we have described early prototypes of a Collaborative Online Visualization and Steering (COVS) Framework in Grids that performs both -simulation and visualization -at the same time (online) to increase the efficiency of e-Scientists. This paper evaluates the evolved mature reference implementation of the COVS framework design that is ready for production usage within Web service-based Grid and e-Science infrastructures.

VISIT/GS: Higher Level Grid Services for Scientific Collaborative Online Visualization and Steering in UNICORE Grids

Many production Grid infrastructures such as DEISA, EGEE, or TeraGrid have begun to offer services to endusers that include access to computational resources. The major goal of these infrastructures is to facilitate the routine interaction of scientists and their workflows with advanced tools and seamless access to computational resources via Grid middleware systems such as UNICORE, gLite or Globus Toolkits. While UNICORE 5 is used in production Grids since several years, recently an early prototype of the new Web services-based UNICORE 6 became available that will be continuously improved in the next months for its use in production. In absence of a widely accepted framework for visualization and steering, the new UNICORE 6 Grid middleware provides not such a higher level service by default. This motivates this contribution to support e-Scientists in upcoming WS-based UNICORE Grids with visualization and steering techniques. In this paper we present the augmentation of the early standards-based UNICORE 6 prototype with a higher-level service for collaborative online visualization and steering. It describes the seamless integration of this service within UNICORE Grids by retaining the convenient single sign-on feature.