Massively Parallel Computing and the Search for Jets and Black Holes at the LHC

Massively parallel computing at the LHC could be the next leap necessary to reach an era of new discoveries at the LHC after the Higgs discovery. Scientific computing is a critical component of the LHC experiment, including operation, trigger, LHC computing GRID, simulation, and analysis. One way to improve the physics reach of the LHC is to take advantage of the flexibility of the trigger system by integrating coprocessors based on Graphics Processing Units (GPUs) or the Many Integrated Core (MIC) architecture into its server farm. This cutting edge technology provides not only the means to accelerate existing algorithms, but also the opportunity to develop new algorithms that select events in the trigger that previously would have evaded detection. In this article we describe new algorithms that would allow to select in the trigger new topological signatures that include non-prompt jet and black hole--like objects in the silicon tracker.Comment: 15 pages, 11 figures, submitted to NIM

First Evaluation of the CPU, GPGPU and MIC Architectures for Real Time Particle Tracking based on Hough Transform at the LHC

Recent innovations focused around {\em parallel} processing, either through systems containing multiple processors or processors containing multiple cores, hold great promise for enhancing the performance of the trigger at the LHC and extending its physics program. The flexibility of the CMS/ATLAS trigger system allows for easy integration of computational accelerators, such as NVIDIA's Tesla Graphics Processing Unit (GPU) or Intel's \xphi, in the High Level Trigger. These accelerators have the potential to provide faster or more energy efficient event selection, thus opening up possibilities for new complex triggers that were not previously feasible. At the same time, it is crucial to explore the performance limits achievable on the latest generation multicore CPUs with the use of the best software optimization methods. In this article, a new tracking algorithm based on the Hough transform will be evaluated for the first time on a multi-core Intel Xeon E5-2697v2 CPU, an NVIDIA Tesla K20c GPU, and an Intel \xphi\ 7120 coprocessor. Preliminary time performance will be presented.Comment: 13 pages, 4 figures, Accepted to JINS

Remodeler Catalyzed Nucleosome Repositioning: Influence of Structure and Stability

The packaging of the eukaryotic genome into chromatin regulates the storage of genetic information, including the access of the cell’s DNA metabolism machinery. Indeed, since the processes of DNA replication, translation, and repair require access to the underlying DNA, several mechanisms, both active and passive, have evolved by which chromatin structure can be regulated and modified. One mechanism relies upon the function of chromatin remodeling enzymes which couple the free energy obtained from the binding and hydrolysis of ATP to the mechanical work of repositioning and rearranging nucleosomes. Here, we review recent work on the nucleosome mobilization activity of this essential family of molecular machines

The Influence of 150-Cavity Binders on the Dynamics of Influenza A Neuraminidases as Revealed by Molecular Dynamics Simulations and Combined Clustering

Neuraminidase inhibitors are the main pharmaceutical agents employed for treatments of influenza infections. The neuraminidase structures typically exhibit a 150-cavity, an exposed pocket that is adjacent to the catalytic site. This site offers promising additional contact points for improving potency of existing pharmaceuticals, as well as generating entirely new candidate inhibitors. Several inhibitors based on known compounds and designed to interact with 150-cavity residues have been reported. However, the dynamics of any of these inhibitors remains unstudied and their viability remains unknown. This work reports the outcome of long-term, all-atom molecular dynamics simulations of four such inhibitors, along with three standard inhibitors for comparison. Each is studied in complex with four representative neuraminidase structures, which are also simulated in the absence of ligands for comparison, resulting in a total simulation time of 9.6µs. Our results demonstrate that standard inhibitors characteristically reduce the mobility of these dynamic proteins, while the 150-binders do not, instead giving rise to many unique conformations. We further describe an improved RMSD-based clustering technique that isolates these conformations – the structures of which are provided to facilitate future molecular docking studies – and reveals their interdependence. We find that this approach confers many advantages over previously described techniques, and the implications for rational drug design are discussed

Mathematical Methods for studying DNA and Protein Interactions

Deoxyribnucleic Acid (DNA) damage can lead to health related issues such as developmental disorders, aging, and cancer. It has been estimated that damage rates may be as high as 100,000 per cell per day. Because of the devastating effects that DNA damage can have, DNA repair mechanisms are of great interest yet are not completely understood. To gain a better understanding of possible DNA repair mechanisms, my dissertation focused on mathematical methods for understanding the interactions between DNA and proteins. I developed a damaged DNA model to estimate the probabilities of damaged DNA being located at specific positions. Experiments were then performed that suggested that the damaged DNA may be repositioned. These experimental results were consistent with the model's prediction that damaged DNA has preferred locations. To study how proteins might be moving along the DNA, I studied the use of the uniform motion “n-step” model. The n-step model has been used to determine the kinetics parameters (e.g. rates at which a protein moves along the DNA, how much energy is required to move a protein along a specified amount of DNA, etc.) of proteins moving along the DNA. Monte Carlo methods were used to simulate proteins moving with different types of non-uniform motion (e.g. backward, jumping, etc.) along the DNA. Estimates for the kinetics parameters in the n-step model were found by fitting of the Monte Carlo simulation data. Analysis indicated that non-uniform motion of the protein may lead to over or underestimation of the kinetic parameters of this n-step model

GPU Enhancement of the Trigger to Extend Physics Reach at the Large Hadron Collider

At the Large Hadron Collider (LHC), the trigger systems for the detectors must be able to process a very large amount of data in a very limited amount of time, so that the nominal collision rate of 40 MHz can be reduced to a data rate that can be stored and processed in a reasonable amount of time. This need for high performance places very stringent requirements on the complexity of the algorithms that can be used for identifying events of interest in the trigger system, which potentially limits the ability to trigger on signatures of various new physics models. In this paper, we present an alternative tracking algorithm, based on the Hough transform, which avoids many of the problems associated with the standard combinatorial track finding currently used. The Hough transform is also well-adapted for Graphics Processing Unit (GPU)-based computing, and such GPU-based systems could be easily integrated into the existing High-Level Trigger (HLT). This algorithm offers the ability to trigger on topological signatures of new physics currently not practical to reconstruct, such as events with jets or black holes significantly displaced from the primary vertex. This paper presents, for the first time, an implementation and preliminary performance results using NVIDIA Tesla C2075 and K20c GPUs.Comment: 5 pages, 3 figures. Submitted to proceedings of the 20th International Conference on Computing in High Energy and Nuclear Physics (CHEP2013), Amsterda

Calculus-enhanced energy-first curriculum for introductory physics improves student performance locally and in downstream courses

Here we demonstrate the benefits of a new curriculum for introductory calculus-based physics that motivates classical mechanics using a modified version of Hamiltonian mechanics. This curriculum shifts the initial focus of instruction away from forces and the associated vector mathematics, which are known to be problematic for students, to the scalar quantity energy, which is more closely aligned with their previously established intuition, and associated differential and integral calculus. We show that implementation of this calculus-enhanced “energy-first” curriculum resulted in higher normalized gains on the Force Concept Inventory exam for all students and improved performance in downstream engineering courses for students with lower ACT math scores. In other words, the downstream benefits were largest for students with lower math abilities who also pose a larger retention risk. This new curriculum thus has the potential to improve student retention by specifically helping the students who need help the most, including traditionally underserved populations who often have weaker mathematics preparation. We propose future work to investigate whether this new curriculum has lowered the math transference barrier to learning in introductory physics, resulting concomitantly in improvements in student learning of classical mechanics and in student fluency with applied mathematics.Northrop Grumman Foundatio

Effects of nucleosome stability on remodeler-catalyzed repositioning

Chromatin remodelers are molecular motors that play essential roles in the regulation of nucleosome positioning and chromatin accessibility. These machines couple the energy obtained from the binding and hydrolysis of ATP to the mechanical work of manipulating chromatin structure through processes that are not completely understood. Here we present a quantitative analysis of nucleosome repositioning by the imitation switch (ISWI) chromatin remodeler and demonstrate that nucleosome stability significantly impacts the observed activity. We show how DNA damage induced changes in the affinity of DNA wrapping within the nucleosome can affect ISWI repositioning activity and demonstrate how assay-dependent limitations can bias studies of nucleosome repositioning. Together, these results also suggest that some of the diversity seen in chromatin remodeler activity can be attributed to the variations in the thermodynamics of interactions between the remodeler, the histones, and the DNA, rather than reflect inherent properties of the remodeler itself