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© 2015 The Authors Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association. Objective Identification of a particular cause of meningoencephalitis can be challenging owing to the myriad bacteria, viruses, fungi, and parasites that can produce overlapping clinical phenotypes, frequently delaying diagnosis and therapy. Metagenomic deep sequencing (MDS) approaches to infectious disease diagnostics are known for their ability to identify unusual or novel viruses and thus are well suited for investigating possible etiologies of meningoencephalitis. Methods We present the case of a 74-year-old woman with endophthalmitis followed by meningoencephalitis. MDS of her cerebrospinal fluid (CSF) was performed to identify an infectious agent. Results Sequences aligning to Balamuthia mandrillaris ribosomal RNA genes were identified in the CSF by MDS. Polymerase chain reaction subsequently confirmed the presence of B. mandrillaris in CSF, brain tissue, and vitreous fluid from the patient's infected eye. B. mandrillaris serology and immunohistochemistry for free-living amoebas on the brain biopsy tissue were positive. Interpretation The diagnosis was made using MDS after the patient had been hospitalized for several weeks and subjected to costly and invasive testing. MDS is a powerful diagnostic tool with the potential for rapid and unbiased pathogen identification leading to early therapeutic targeting.

The performance of parallel computer code depends on an intricate interplay of the processors, the architecture of the compute nodes, their interconnect network, the numerical algorithm, and the scheduling policy used. This note considers a case study of a solver of a system of transient hyperbolic conservation laws which utilizes both point-to-point and collective communications between parallel processes at each time step. The solver is already known to scale well to many parallel processes on distributed-memory clusters with a high performance interconnect network. The results presented here show excellent overall performance of the new cluster hpc with InfiniBand interconnect and confirm that is beneficial to use the maximum number of cores possible on every node, allowing a total of 128 parallel processes on the 32 compute nodes.

During the manufacture of integrated circuits, the process of atomic layer deposition (ALD) is used to deposit a uniform seed layer of solid material atop the surface of a silicon wafer. The process can be modeled on the molecular level by a system of transient, linear integro-partial di erential Boltzmann equations, coupled with a non-linear surface reaction model, together called the kinetic transport and reaction model (KTRM). Each Boltzmann equation can be approximated by discretizing the velocity space, which yields a system of transient hyperbolic conservation laws that only involve the position vector and time as independent variables. The system can then be solved with DG, a computer implementation of the discontinuous Galerkin method. Due to the large size of the systems being solved and large number of time steps required, it is necessary to use parallel computing to obtain a solution in a reasonable amount of time. We analyze the performance of the DG code on multiple mesh resolutions by measuring its speedup and e ciency on UMBC's new distributed-memory cluster, hpc (www.umbc.edu/hpcf). We also compare the performance of DG when it is compiled using the MVAPICH2 and OpenMPI implementations of MPI, the most prevalent parallel communication library today. Testing on a variety of mesh sizes shows that the MVAPICH2 implementation runs as fast or faster than OpenMPI in all cases. This senior thesis is part of undergraduate research conducted under the direction of Dr. Matthias K. Gobbert.