An Implementation of Replica Exchange with Dynamical Scaling for Efficient Large-Scale Simulations.

An implementation of the replica exchange with dynamical scaling (REDS) method in the commonly used molecular dynamics program GROMACS is presented. REDS is a replica exchange method that requires fewer replicas than conventional replica exchange while still providing data over a range of temperatures and can be used in either constant volume or constant pressure ensembles. Details for running REDS simulations are given, and an application to the human islet amyloid polypeptide (hIAPP) 11-25 fragment shows that the model efficiently samples conformational space.

Impact of Interdisciplinary Outpatient Specialty Palliative Care on Survival and Quality of Life in Adults With Advanced Cancer: A Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: In advanced cancer, patients want to know how their care options may affect survival and quality of life, but the impact of outpatient specialty palliative care on these outcomes in cancer is uncertain. PURPOSE: To estimate the impact of outpatient specialty palliative care programs on survival and quality of life in adults with advanced cancer. METHODS: Following PRISMA guidelines, we conducted a systematic review and meta-analysis of randomized controlled trials comparing outpatient specialty palliative care with usual care in adults with advanced cancer. Primary outcomes were 1 year survival and quality of life. Analyses were stratified to compare preliminary studies against higher-quality studies. Secondary outcomes were survival at other endpoints and physical and psychological quality-of-life measures. RESULTS: From 2,307 records, we identified nine studies for review, including five high-quality studies. In the three high-quality studies with long-term survival data (n = 646), patients randomized to outpatient specialty palliative care had a 14% absolute increase in 1 year survival relative to controls (56% vs. 42%, p < .001). The survival advantage was also observed at 6, 9, 15, and 18 months, and median survival was 4.56 months longer (14.55 vs. 9.99 months). In the five high-quality studies with quality-of-life data (n = 1,398), outpatient specialty palliative care improved quality-of-life relative to controls (g = .18, p < .001), including for physical and psychological measures. CONCLUSIONS: Patients with advanced cancer randomized to receive outpatient specialty palliative care lived longer and had better quality of life. Findings have implications for improving care in advanced cancer.

Parallel Maximum Cardinality Matching for General Graphs on GPUs.

The matching problem formulated as Maximum Cardinality Matching in General Graphs (MCMGG) finds the largest matching on graphs without restrictions. The Micali-Vazirani algorithm has the best asymptotic complexity for solving MCMGG when the graphs are sparse. Parallelizing matching in general graphs on the GPU is difficult for multiple reasons. First, the augmenting path procedure is highly recursive, and NVIDIA GPUs use registers to store kernel arguments, which eventually spill into cached device memory, with a performance penalty. Second, extracting parallelism from the matching process requires partitioning the graph to avoid any overlapping augmenting paths. We propose an implementation of the Micali-Vazirani algorithm which identifies bridge edges using thread-parallel breadth-first search, followed by block-parallel path augmentation and blossom contraction. Augmenting path and Union-find methods were implemented as stack-based iterative methods, with a stack allocated in shared memory. Our experimentation shows that compared to the serial implementation, our approach results in up to 15-fold speed-up for very sparse regular graphs, up to 5-fold slowdown for denser regular graphs, and finally a 50-fold slowdown for power-law distributed Kronecker graphs. This implementation has been open-sourced for further research on developing combinatorial graph algorithms on GPUs.

Shared-Memory Parallel Edmonds Blossom Algorithm for Maximum Cardinality Matching in General Graphs.

The Edmonds Blossom algorithm is implemented here using depth-first search, which is intrinsically serial. By streamlining the code, our serial implementation is consistently three to five times faster than the previously fastest general graph matching code. By extracting parallelism across iterations of the algorithm, with coarse-grain locking, we are able to further reduce the run time on random regular graphs four-fold and obtain a two-fold reduction of run time on real-world graphs with similar topology. Solving very sparse graphs (average degree less than four) exhibiting community structure with eight threads led to a slow down of three-fold, but this slow down is replaced by marginal speed up once the average degree is greater than four. We conclude that our parallel coarse-grain locking implementation performs well when extracting parallelism from this augmenting-path-based algorithm and may work well for similar algorithms.

py-MCMD: Python Software for Performing Hybrid Monte Carlo/Molecular Dynamics Simulations with GOMC and NAMD.

py-MCMD, an open-source Python software, provides a robust workflow layer that manages communication of relevant system information between the simulation engines NAMD and GOMC and generates coherent thermodynamic properties and trajectories for analysis. To validate the workflow and highlight its capabilities, hybrid Monte Carlo/molecular dynamics (MC/MD) simulations are performed for SPC/E water in the isobaric-isothermal (NPT) and grand canonical (GC) ensembles as well as with Gibbs ensemble Monte Carlo (GEMC). The hybrid MC/MD approach shows close agreement with reference MC simulations and has a computational efficiency that is 2 to 136 times greater than traditional Monte Carlo simulations. MC/MD simulations performed for water in a graphene slit pore illustrate significant gains in sampling efficiency when the coupled-decoupled configurational-bias MC (CD-CBMC) algorithm is used compared with simulations using a single unbiased random trial position. Simulations using CD-CBMC reach equilibrium with 25 times fewer cycles than simulations using a single unbiased random trial position, with a small increase in computational cost. In a more challenging application, hybrid grand canonical Monte Carlo/molecular dynamics (GCMC/MD) simulations are used to hydrate a buried binding pocket in bovine pancreatic trypsin inhibitor. Water occupancies produced by GCMC/MD simulations are in close agreement with crystallographically identified positions, and GCMC/MD simulations have a computational efficiency that is 5 times better than MD simulations. py-MCMD is available on GitHub at https://github.com/GOMC-WSU/py-MCMD.

Complex Left Atrial Appendage Morphology Is an Independent Risk Factor for Cryptogenic Ischemic Stroke.

Importance: Ischemic strokes pose a significant health burden. However, the etiology of between 20 and 40% of these events remains unknown. Left atrial appendage morphology may influence the occurrence of thromboembolic events. Design: A retrospective cross-sectional study was conducted to investigate the role of LAA morphology in patients with atrial fibrillation (AF) and cardioembolic-associated stroke and patients with cryptogenic stroke without atrial fibrillation. LAA morphology is classified into two groups: (1) simple (chicken-wing) vs. (2) complex (non-chicken wing) based on transesophageal echocardiography (TEE) findings. In addition to the LAA morphology, left atrial parameters, including orifice diameter, depth, emptying velocity, and filling velocity, were collected for both groups. Mathematical, computational models were constructed to investigate flow velocities in chicken-wing and non-chicken wing morphological patterns to assess LAA function further. Findings: TEE values for volume, size, emptying, and filling velocities were similar between simple and complex LAA morphology groups. Patients with cryptogenic stroke without coexisting AF were noted to have significantly higher rates of complex LAA morphology. Chicken-wing LAA morphology was associated with four-fold higher flow rate (kg/s) in computational simulations. Conclusions: Complex LAA morphology may be an independent contributing factor for cryptogenic strokes. Further studies are warranted to investigate the mechanism involved in LAA morphology and thromboembolic events.