VLDB 2026 Research / reviewers in the wild / expert
Tony Printezis
dblp:p/TPrintezis
· DBLP profile ↗
6ranked-venue papers
5as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 6 · 5 first-author
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.
| Software engineering, system software, and programming languages
1 paper |
Runtime systems and virtual machines · 50% Operating systems · 50% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Performance modeling and evaluation · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Runtime systems and virtual machines
garbage collection |
0.0 | 1 | 2002 | GCspy: an adaptable heap visualisation framework · OOPSLA 2002 |
Operating systems › resource management
memory management |
0.0 | 1 | 2002 | GCspy: an adaptable heap visualisation framework · OOPSLA 2002 |
Visualization and visual analytics › software visualization
program behavior visualization |
0.0 | 1 | 2002 | GCspy: an adaptable heap visualisation framework · OOPSLA 2002 |
Performance modeling and evaluation
workload characterization |
0.0 | 1 | 2002 | GCspy: an adaptable heap visualisation framework · OOPSLA 2002 |
Methods — techniques the papers use, named apart from their topics
visualization framework · 0.1data-gathering API · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Use of the JVM at twitter: a bird's eye viewabstractSpecialties:15+ years of virtual machine implementation experience with special focus on memory management / garbage collection. Close to 20 years of C/C++ experience. 15+ years of Java experience. Expert in concurrent/parallel programming. Tony Printezis |
ISMM | 1 |
| 2006 | On measuring garbage collection responsiveness
Tony Printezis |
Sci. Comput. Program. | 1 |
| 2004 | Garbage-first garbage collectionabstractGarbage-First is a server-style garbage collector, targeted for multi-processors with large memories, that meets a soft real-time goal with high probability, while achieving high throughput. Whole-heap operations, such as global marking, are performed concurrently with mutation, to prevent interruptions proportional to heap or live-data size. Concurrent marking both provides collection ”completeness ” and identifies regions ripe for reclamation via compacting evacuation. This evacuation is performed in parallel on multiprocessors, to increase throughput. David Detlefs, Christine H. Flood, Steve Heller, Tony Printezis |
ISMM | 4 |
| 2002 | GCspy: an adaptable heap visualisation frameworkabstractGCspy is an architectural framework for the collection, transmission, storage and replay of memory management behaviour. It makes new contributions to the understanding of the dynamic memory behaviour of programming languages (and especially object-oriented languages that make heavy demands on the performance of memory managers). GCspy's architecture allows easy incorporation into any memory management system: it is not limited to garbage-collected languages. It requires only small changes to the system in which it is incorporated but provides a simple to use yet powerful data-gathering API. GCspy scales to allow very large heaps to be visualised effectively and efficiently. It allows already-running, local or remote systems to be visualised and those systems to run at full speed outside the points at which data is gathered. GCspy's visualisation tool presents this information in a number of novel ways.Deep understanding of program behaviour is essential to the design of the next generation of garbage collectors and explicit allocators. Until now, no satisfactory tools have been available to assist the implementer in gaining an understanding of heap behaviour. GCspy has been demonstrated to be a practical solution to this dilemma. It has been used to analyse production Java virtual machines running applications of realistic sizes. Its use has revealed important insights into the interaction between application program and JVM and has led to the development of better garbage collectors. Tony Printezis, Richard E. Jones |
OOPSLA | 1 |
| 2001 | An efficient object promotion algorithm for persistent object systemsabstractAbstract We report on a bulk object‐loading algorithm for persistent object stores calledGhosted Allocation. It allocates large numbers of objects in a persistent store atomically, efficiently, and reliably. Its main strengths are that it minimizes I/O traffic, optimizes the disk access pattern, and does not impose complex requirements on applications. Our experiments demonstrate that theGhosted Allocationalgorithm is efficient and most importantly scalable, sustaining allocation rates of up to 63 000 objects s‐1. Copyright © 2001 John Wiley & Sons, Ltd. Tony Printezis, Malcolm P. Atkinson 0001 |
Softw. Pract. Exp. | 1 |
| 2000 | A Generational Mostly-Concurrent Garbage CollectorabstractThis paper reports our experiences with a mostly-concurrent incremental garbage collector, implemented in the context of a high performance virtual machine for the Java™ programming language. The garbage collector is based on the “mostly parallel” collection algorithm of Boehm et al. and can be used as the old generation of a generational memory system. It overloads efficient write-barrier code already generated to support generational garbage collection to also identify objects that were modified during concurrent marking. These objects must be rescanned to ensure that the concurrent marking phase marks all live objects. This algorithm minimises maximum garbage collection pause times, while having only a small impact on the average garbage collection pause time and overall execution time. We support our claims with experimental results, for both a synthetic benchmark and real programs. Tony Printezis, David Detlefs |
ISMM | 1 |