Randomly stopped sums with consistently varying distributions

In our thesis we analyze one class of heavy-tailed distributions. Distributions belonging to this class have consistently varying tails. Let {X_1, X_2, ...} be a sequence of independent but not necessarily identically distributed non-negative random variables, a number of which has distribution functions with consistently varying tails. Let N be a counting random variable independent of {X_1, X_2, ...}. We found conditions for random variables {X_1, X_2, ...} and N, under which distribution of the randomly stopped sum X_1 + X_2 + ... + X_N preserves consistently varying tail. Our results could be useful when analysing the critical characteristics of risk models

The exponential estimate of the ultimate ruin probability for the non-homogeneous renewal risk model

In this work, the non-homogeneous risk model is considered. In such a model, claims and inter-arrival times are independent but possibly non-identically distributed. The easily verifiable conditions are found such that the ultimate ruin probability of the model satisfies the exponential estimate exp{−ϱu} for all values of the initial surplus u⩾0. Algorithms to estimate the positive constant ϱ are also presented. In fact, these algorithms are the main contribution of this work. Sharpness of the derived inequalities is illustrated by several numerical examples

Randomly stopped sums with consistently varying distributions

Let {ξ1, ξ2, . . .} be a sequence of independent random variables, and η be a counting random variable independent of this sequence. We consider conditions for {ξ1, ξ2, . . .} and η under which the distribution function of the random sum Sη = ξ1 + ξ2 + ·· ·+ξη belongs to the class of consistently varying distributions. In our consideration, the random variables {ξ1, ξ2, . . .} are not necessarily identically distributed

Evolution of the CMS Global Submission Infrastructure for the HL-LHC Era

Efforts in distributed computing of the CMS experiment at the LHC at CERN are now focusing on the functionality required to fulfill the projected needs for the HL-LHC era. Cloud and HPC resources are expected to be dominant relative to resources provided by traditional Grid sites, being also much more diverse and heterogeneous. Handling their special capabilities or limitations and maintaining global flexibility and efficiency, while also operating at scales much higher than the current capacity, are the major challenges being addressed by the CMS Submission Infrastructure team. These proceedings discuss the risks to the stability and scalability of the CMS HTCondor infrastructure extrapolated to such a scenario, thought to be derived mostly from its growing complexity, with multiple Negotiators and schedulers flocking work to multiple federated pools. New mechanisms for enhanced customization and control over resource allocation and usage, mandatory in this future scenario, are also described

Evolution of the CMS Global Submission Infrastructure for the HL-LHC Era

Efforts in distributed computing of the CMS experiment at the LHC at CERN are now focusing on the functionality required to fulfill the projected needs for the HL-LHC era. Cloud and HPC resources are expected to be dominant relative to resources provided by traditional Grid sites, being also much more diverse and heterogeneous. Handling their special capabilities or limitations and maintaining global flexibility and efficiency, while also operating at scales much higher than the current capacity, are the major challenges being addressed by the CMS Submission Infrastructure team. These proceedings discuss the risks to the stability and scalability of the CMS HTCondor infrastructure extrapolated to such a scenario, thought to be derived mostly from its growing complexity, with multiple Negotiators and schedulers flocking work to multiple federated pools. New mechanisms for enhanced customization and control over resource allocation and usage, mandatory in this future scenario, are also described

Exploiting CRIC to streamline the configuration management of GlideinWMS factories for CMS support

GlideinWMS is a workload management and provisioning system that allows sharing computing resources distributed over independent sites. Based on the requests made by GlideinWMS frontends, a dynamically sized pool of resources is created by GlideinWMS pilot factories via pilot job submission to resource sites’ CEs. More than 400 CEs are currently serving more than ten virtual organizations through GlideinWMS, with CMS being the biggest user with 230 CEs. The complex configurations of the parameters defining resource requests, as submitted to those CEs, have been historically managed by manually editing a set of different XML files. New possibilities arise with CMS adopting the CRIC, an information system that collects, aggregates, stores, and exposes, among other things, computing resource data coming from various data providers. The paper will describe the challenges faced when CMS started to use CRIC to automatically generate the GlideinWMS factory configurations. The architecture of the prototype, and the ancillary tools developed to ease this transition, will be discussed. Finally, future plans and milestones will be outlined

Exploiting CRIC to streamline the configuration management of GlideinWMS factories for CMS support

GlideinWMS is a workload management and provisioning system that allows sharing computing resources distributed over independent sites. Based on the requests made by GlideinWMS frontends, a dynamically sized pool of resources is created by GlideinWMS pilot factories via pilot job submission to resource sites’ CEs. More than 400 CEs are currently serving more than ten virtual organizations through GlideinWMS, with CMS being the biggest user with 230 CEs. The complex configurations of the parameters defining resource requests, as submitted to those CEs, have been historically managed by manually editing a set of different XML files. New possibilities arise with CMS adopting the CRIC, an information system that collects, aggregates, stores, and exposes, among other things, computing resource data coming from various data providers. The paper will describe the challenges faced when CMS started to use CRIC to automatically generate the GlideinWMS factory configurations. The architecture of the prototype, and the ancillary tools developed to ease this transition, will be discussed. Finally, future plans and milestones will be outlined