High-Throughput Computing on High-Performance Platforms: A Case Study

The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan---a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i) a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner

Disassembly of Large Composite-Rich Installations

Considering the demanufacturing of large infrastructures (as wind blades and aircrafts) rich in composite materials, the most impacting step in terms of costs is disassembly. Different routes could be followed for dismantling and transportation and several factors influence the final result (as the technology used, the logistic and the administrative issues). For this reason, it is fundamental to understand which solution has to be followed to reduce the impact of decommissioning on the overall recycling and reusing cost. This work, after the formalization of the different possible disassembly scenarios, proposes a Decision Support System (DSS) for disassembly of large composite-rich installations, that has been designed and implemented for the identification of the most promising disassembly strategy, according to the process costs minimization. The mathematical models constituting the core of this tool are detailed and the DSS is applied to disassembly of onshore wind blades, underling the importance of similar systems to optimize demanufacturing costs

Constructing Matrix Exponential Distributions by Moments and Behavior around Zero

This paper deals with moment matching of matrix exponential (ME) distributions used to approximate general probability density functions (pdf). A simple and elegant approach to this problem is applying Padé approximation to the moment generating function of the ME distribution. This approach may, however, fail if the resulting ME function is not a proper probability density function; that is, it assumes negative values. As there is no known, numerically stable method to check the nonnegativity of general ME functions, the applicability of Padé approximation is limited to low-order ME distributions or special cases. In this paper, we show that the Padé approximation can be extended to capture the behavior of the original pdf around zero and this can help to avoid representations with negative values and to have a better approximation of the shape of the original pdf. We show that there exist cases when this extension leads to ME function whose nonnegativity can be verified, while the classical approach results in improper pdf. We apply the ME distributions resulting from the proposed approach in stochastic models and show that they can yield more accurate results

Family history of cancer as surrogate predictor for immunotherapy with anti-PD1/PD-L1 agents: preliminary report of the FAMI-L1 study.

Aim: Tumors related to hereditary susceptibility seem to have an immunosensitive phenotype. Materials & methods: We conducted a multicenter retrospective study, to investigate if family history of cancer, multiple neoplasms and early onset of cancer could be related to clinical outcomes of anti-PD-1/PD-L1 therapy. Activity and efficacy data of 211 advanced cancer patients (kidney, non-small-cell lung cancer, melanoma, urothelium, colorectal and HeN), treated at seven Italian centers with anti-PD-1/PD-L1 agents, were analyzed. Results: In this preliminary report at multivariate analyses, positive family history of cancer showed a statistically significant relationship with a better objective response rate (p = 0.0024), disease control rate (p = 0.0161), median time to treatment failure (p = 0.0203) and median overall survival (p = 0.0221). Diagnosis of multiple neoplasms significantly correlates only to a better disease control rate, while interestingly non-early onset of cancer and sex (in favor of female patients) showed significant correlation with a better median overall survival (p = 0.0268 and p = 0.0272, respectively). Conclusion: This pilot study seems to individuate easily available patient's features as possible predictive surrogates of clinical benefit for anti-PD-1/PD-L1 treatments. These preliminary results need to be confirmed with a greater sample size, in prospective trials with immunotherapy