2,140 research outputs found
Scalable Global Grid catalogue for LHC Run3 and beyond
The AliEn (ALICE Environment) file catalogue is a global unique namespace
providing mapping between a UNIX-like logical name structure and the
corresponding physical files distributed over 80 storage elements worldwide.
Powerful search tools and hierarchical metadata information are integral parts
of the system and are used by the Grid jobs as well as local users to store and
access all files on the Grid storage elements. The catalogue has been in
production since 2005 and over the past 11 years has grown to more than 2
billion logical file names. The backend is a set of distributed relational
databases, ensuring smooth growth and fast access. Due to the anticipated fast
future growth, we are looking for ways to enhance the performance and
scalability by simplifying the catalogue schema while keeping the functionality
intact. We investigated different backend solutions, such as distributed key
value stores, as replacement for the relational database. This contribution
covers the architectural changes in the system, together with the technology
evaluation, benchmark results and conclusions.Comment: Proceedings of the 22nd International Conference on Computing in High
Energy and Nuclear Physics, CHEP 2016, 10-14 October 2016, San Francisco.
Submitted to Journal of Physics: Conference Series (JPCS
A Security Monitoring Framework For Virtualization Based HEP Infrastructures
High Energy Physics (HEP) distributed computing infrastructures require
automatic tools to monitor, analyze and react to potential security incidents.
These tools should collect and inspect data such as resource consumption, logs
and sequence of system calls for detecting anomalies that indicate the presence
of a malicious agent. They should also be able to perform automated reactions
to attacks without administrator intervention. We describe a novel framework
that accomplishes these requirements, with a proof of concept implementation
for the ALICE experiment at CERN. We show how we achieve a fully virtualized
environment that improves the security by isolating services and Jobs without a
significant performance impact. We also describe a collected dataset for
Machine Learning based Intrusion Prevention and Detection Systems on Grid
computing. This dataset is composed of resource consumption measurements (such
as CPU, RAM and network traffic), logfiles from operating system services, and
system call data collected from production Jobs running in an ALICE Grid test
site and a big set of malware. This malware was collected from security
research sites. Based on this dataset, we will proceed to develop Machine
Learning algorithms able to detect malicious Jobs.Comment: Proceedings of the 22nd International Conference on Computing in High
Energy and Nuclear Physics, CHEP 2016, 10-14 October 2016, San Francisco.
Submitted to Journal of Physics: Conference Series (JPCS
Run-time reconfigurable acceleration for genetic programming fitness evaluation in trading strategies
Genetic programming can be used to identify complex patterns in financial markets which may lead to more advanced trading strategies. However, the computationally intensive nature of genetic programming makes it difficult to apply to real world problems, particularly in real-time constrained scenarios. In this work we propose the use of Field Programmable Gate Array technology to accelerate the fitness evaluation step, one of the most computationally demanding operations in genetic programming. We propose to develop a fully-pipelined, mixed precision design using run-time reconfiguration to accelerate fitness evaluation. We show that run-time reconfiguration can reduce resource consumption by a factor of 2 compared to previous solutions on certain configurations. The proposed design is up to 22 times faster than an optimised, multithreaded software implementation while achieving comparable financial returns
Thermal transport in nanoelectronic devices cooled by on-chip magnetic refrigeration
On-chip demagnetization refrigeration has recently emerged as a powerful tool
for reaching microkelvin electron temperatures in nanoscale structures. The
relative importance of cooling on-chip and off-chip components and the thermal
subsystem dynamics are yet to be analyzed. We study a Coulomb blockade
thermometer with on-chip copper refrigerant both experimentally and
numerically, showing that dynamics in this device are captured by a
first-principles model. Our work shows how to simulate thermal dynamics in
devices down to microkelvin temperatures, and outlines a recipe for a
low-investment platform for quantum technologies and fundamental nanoscience in
this novel temperature range.Comment: 11 pages, 10 figure
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