Tri-Lab data models and format (DMF) project: parallel I/O and data exchange

A central goal of the ASCI program is to push simulation and modeling for Science-based Stockpile Stewardship to unprecedented levels. ASCI applications will use extremely high-fidelity models, on the order of one billion cells, to generate terabytes of raw data. Such vast amounts of data produced by these supercomputing applications will overwhelm scientists, whose efforts to understand their results are hindered by inadequate visualization and data management tools. Much of the Scientific Data Management (SDM) effort concerns managing the large and complex data emerging from these simulation codes. One particular area for which commercial and scalable solutions do not exist is in Parallel I/O and data exchange between simulations. To address these needs, the Tri-lab Data Models and Formats effort of the SDM project is developing capabilities to enable the capturing and sharing of simulation data

Parallelizing Monte Carlo with PMC

PMC (Parallel Monte Carlo) is a system of generic interface routines that allows easy porting of Monte Carlo packages of large-scale physics simulation codes to Massively Parallel Processor (MPP) computers. By loading various versions of PMC, simulation code developers can configure their codes to run in several modes: serial, Monte Carlo runs on the same processor as the rest of the code; parallel, Monte Carlo runs in parallel across many processors of the MPP with the rest of the code running on other MPP processor(s); distributed, Monte Carlo runs in parallel across many processors of the MPP with the rest of the code running on a different machine. This multi-mode approach allows maintenance of a single simulation code source regardless of the target machine. PMC handles passing of messages between nodes on the MPP, passing of messages between a different machine and the MPP, distributing work between nodes, and providing independent, reproducible sequences of random numbers. Several production codes have been parallelized under the PMC system. Excellent parallel efficiency in both the distributed and parallel modes results if sufficient workload is available per processor. Experiences with a Monte Carlo photonics demonstration code and a Monte Carlo neutronics package are described

Vorinostat in advanced prostate cancer patients progressing on prior chemotherapy (National Cancer Institute Trial 6862)

BACKGROUND: This phase 2 trial was designed to evaluate the efficacy of vorinostat in chemotherapy-pretreated patients with metastatic castration-resistant prostate cancer. METHODS: Patients with disease progression on 1 prior chemotherapy, a prostate-specific antigen (PSA) ≥5 ng/mL, and adequate organ function were treated with 400 mg vorinostat orally daily. The primary endpoint was the 6-month progression rate. Secondary endpoints included safety, rate of PSA decline, objective response, overall survival, and effects of vorinostat on serum interleukin-6 (IL-6) levels. RESULTS: Twenty-seven eligible patients were accrued. The median number of cycles delivered was 2 (range, 1-7). All patients were taken off therapy before 6 months. The best objective response in the eligible patient was stable disease in 2 (7%) patients. No PSA decline of ≥50% was observed. There was 1 grade 4 adverse event (AE), and 44% of patients experienced grade 3 adverse events. The most common adverse events were fatigue (81%), nausea (74%), anorexia (59%), vomiting (33%), diarrhea (33%), and weight loss (26%). Median time to progression and overall survival were 2.8 and 11.7 months, respectively. Median IL-6 levels (pg/mL) were higher in patients removed from the protocol for toxicity compared with progression at all time points, including baseline (5.2 vs 2.1, P = .02), Day 15 Cycle 1 (9.5 vs 2.2, P = .01), Day 1 Cycle 2 (9.8 vs 2.2, P = .01), and end of study (11.0 vs 2.9, P = .09). CONCLUSIONS: Vorinostat at this dose was associated with significant toxicities limiting efficacy assessment in this patient population. The significant association between IL-6 levels and removal from the study for toxicities warrants further investigation. Cancer 2009. © 2009 American Cancer Society.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64445/1/24597_ftp.pd

Odyssey

We present results obtained with the Odyssey simulation code. Odyssey is a 1, 2, and 3 dimensional AMR code using cartesian, cylindrical, and spherical coordinates. The results provide an interesting snapshot of Odyssey at this point in its development. Results include parallel performance and scaling, Eulerian hydrodynamics algorithm comparisons, ADI based diffusion solvers on hierarchical meshes, ECB treatment of material interfaces in diffusion solves

Neural Reuse and the Nature of Evolutionary Constraints

In humans, the reuse of neural structure is particularly pronounced at short, task-relevant timescales. Here, an argument is developed for the claim that facts about neural reuse at task-relevant timescales conflict with at least one characterization of neural reuse at an evolutionary timescale. It is then argued that, in order to resolve the conflict, we must conceptualize evolutionary-scale reuse more abstractly than has been generally recognized. The final section of the paper explores the relationship between neural reuse and human nature. It is argued that neural reuse is not well-described as a process that constrains our present cognitive capacities. Instead, it liberates those capacities from the ancestral tethers that might otherwise have constrained them

Repurposing Itraconazole as a Treatment for Advanced Prostate Cancer: A Noncomparative Randomized Phase II Trial in Men With Metastatic Castration‐Resistant Prostate Cancer

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139926/1/onco0163-sup-0001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139926/2/onco0163.pd

Schwarz type preconditioners for the neutron diffusion equation

[EN] Domain decomposition is a mature methodology that has been used to accelerate the convergence of partial differential equations. Even if it was devised as a solver by itself, it is usually employed together with Krylov iterative methods improving its rate of convergence, and providing scalability with respect to the size of the problem. In this work, a high order finite element discretization of the neutron diffusion equation is considered. In this problem the preconditioning of large and sparse linear systems arising from a source driven formulation becomes necessary due to the complexity of the problem. On the other hand, preconditioners based on an incomplete factorization are very expensive from the point of view of memory requirements. The acceleration of the neutron diffusion equation is thus studied here by using alternative preconditioners based on domain decomposition techniques inside Schur complement methodology. The study considers substructuring preconditioners, which do not involve overlapping, and additive Schwarz preconditioners, where some overlapping between the subdomains is taken into account. The performance of the different approaches is studied numerically using two-dimensional and three-dimensional problems. It is shown that some of the proposed methodologies outperform incomplete LU factorization for preconditioning as long as the linear system to be solved is large enough, as it occurs for three-dimensional problems. They also outperform classical diagonal Jacobi preconditioners, as long as the number of systems to be solved is large enough in such a way that the overhead of building the pre-conditioner is less than the improvement in the convergence rate. (C) 2016 Elsevier B.V. All rights reserved.The work has been partially supported by the spanish Ministerio de Economía y Competitividad under projects ENE 2014-59442-P and MTM2014-58159-P, the Generalitat Valenciana under the project PROMETEO II/2014/008 and the Universitat Politècnica de València under the project FPI-2013. The work has also been supported partially by the Swedish Research Council (VR-Vetenskapsrådet) within a framework grant called DREAM4SAFER, research contract C0467701.Vidal-Ferràndiz, A.; González Pintor, S.; Ginestar Peiro, D.; Verdú Martín, GJ.; Demazière, C. (2017). Schwarz type preconditioners for the neutron diffusion equation. Journal of Computational and Applied Mathematics. 309:563-574. https://doi.org/10.1016/j.cam.2016.02.056S56357430

Single-scatter Monte Carlo compared to condensed history results for low energy electrons

A Monte Carlo code has been developed to simulate individual electron interactions. The code has been instrumental in determining the range of validity for the widely used condensed history method. This task was accomplished by isolating and testing the condensed history assumptions. The results show that the condensed history method fails for low energy electron transport due to inaccuracies in energy loss and spatial positioning.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29795/1/0000141.pd

LSD1 inhibition attenuates androgen receptor V7 splice variant activation in castration resistant prostate cancer models

Background: Castrate resistant prostate cancer (CRPC) is often driven by constitutively active forms of the androgen receptor such as the V7 splice variant (AR-V7) and commonly becomes resistant to established hormonal therapy strategies such as enzalutamide as a result. The lysine demethylase LSD1 is a co-activator of the wild type androgen receptor and a potential therapeutic target in hormone sensitive prostate cancer. We evaluated whether LSD1 could also be therapeutically targeted in CRPC models driven by AR-V7. Methods: We utilised cell line models of castrate resistant prostate cancer through over expression of AR-V7 to test the impact of chemical LSD1 inhibition on AR activation. We validated findings through depletion of LSD1 expression and in prostate cancer cell lines that express AR-V7. Results: Chemical inhibition of LSD1 resulted in reduced activation of the androgen receptor through both the wild type and its AR-V7 splice variant forms. This was confirmed and validated in luciferase reporter assays, in LNCaP and 22Rv1 prostate cancer cell lines and in LSD1 depletion experiments. Conclusion: LSD1 contributes to activation of both the wild type and V7 splice variant forms of the androgen receptor and can be therapeutically targeted in models of CRPC. Further development of this approach is warranted