Demo Data from VLDB 2026 / reviewers in the wild / expert
Gerardo Ganis
dblp:142/2466
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 41% Distributed systems · 18% Parallel and multicore computing · 18% |
Topics — the 7 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing
cluster computing |
0.1 | 1 | 2006 | PROOF - The Parallel ROOT Facility · HPDC 2006 |
High-performance computing › performance optimization
data access optimization |
0.1 | 1 | 2006 | PROOF - The Parallel ROOT Facility · HPDC 2006 |
Distributed systems › distributed data processing
distributed data analytics |
0.1 | 1 | 2006 | PROOF - The Parallel ROOT Facility · HPDC 2006 |
Parallel and multicore computing › parallel computing
parallel data processing |
0.1 | 1 | 2006 | PROOF - The Parallel ROOT Facility · HPDC 2006 |
Electronic design automation › high-level synthesis
scheduling |
0.1 | 1 | 2006 | PROOF - The Parallel ROOT Facility · HPDC 2006 |
Storage systems
distributed storage |
0.0 | 1 | 2006 | PROOF - The Parallel ROOT Facility · HPDC 2006 |
High-performance computing › cluster computing
heterogeneous clusters |
0.0 | 1 | 2006 | PROOF - The Parallel ROOT Facility · HPDC 2006 |
Methods — techniques the papers use, named apart from their topics
multi-tier architecture · 0.1i/o optimization · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Interactive Exploitation of Nonuniform Cloud Resources for LHC Computing at CERNabstractComputing at LHC is based on the Grid model, where geographically distributed local batch farms are federated using proper middleware. Several computing centers are considering a conversion to private clouds, capable of supporting alternative computing models along with the Grid one: CERN is pioneering such conversion. Computing tasks at LHC are mostly performed using ROOT, a framework for simulation, reconstruction and data analysis. In High Energy Physics (HEP) data are independent physics collision events. PROOF (Parallel ROOT Facility) is a cluster model built on top of ROOT, capable of processing such events interactively and in parallel. Given the increasing availability of cloud resources, running virtual PROOF clusters has become an appealing alternative. We will show how PROOF interactivity naturally fits into the cloud model: in particular by overcoming VM performance diversity via dynamic workload assignment. Several technologies are combined: the CernVM ecosystem provides the base VM image, APIs for cloud federation and a distributed filesystem for LHC software distribution, HTCondor and PROOF on Demand (PoD) control scheduling of leases and affect the lifecycle of VMs opportunistically. We will illustrate the current status of the project, and the conjoint efforts on PROOF and CernVM to create a reference implementation suiting the needs of all LHC experiments. The final product will be a personal and elastic "Analysis Facility as a Service" where the user connects using ROOT itself as standard LHC client. Dario Berzano, Jakob Blomer, Predrag Buncic, Gerardo Ganis, Georgios Lestaris, René Meusel |
IEEE CLOUD | 4 |
| 2006 | PROOF - The Parallel ROOT FacilityabstractThe parallel ROOT facility, PROOF, enables the interactive analysis of distributed data sets in a transparent way. It exploits the inherent parallelism in data sets of uncorrelated events via a multi-tier architecture that optimizes I/O and CPU utilization in heterogeneous clusters with distributed storage. On a grid, PROOF can use the available services to find out the location of data to analyze and the resources to use. Dedicated PROOF-enabled test-beds are now being deployed for testing by the LHC experiments. Being part of the ROOT framework PROOF inherits the benefits of a high performance object-oriented storage system and a wealth of statistical and visualization tools. The basic ideas and architecture underlying the PROOF project are described, together with the status of the project, focusing mostly on the issues of data access optimization, scheduling of user sessions and user interface Bertrand Bellenot, Rene Brun, Gerardo Ganis, Jan Iwaszkiewicz, Guenter Kickinger, Andreas J. Peters, Fons Rademakers, Maarten Ballintijn, C. Loizides, C. Reed, Philippe Canal, Derek Feichtinger |
HPDC | 3 |