VLDB 2026 Research / reviewers in the wild / expert
Yoav Ossia
dblp:15/175
· DBLP profile ↗
5ranked-venue papers
2as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 5 · 2 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
4 papers |
Runtime systems and virtual machines · 90% Operating systems · 10% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 6 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Runtime systems and virtual machines › garbage collection
parallel garbage collection |
0.1 | 3 | 2005 | A parallel, incremental, mostly concurrent garbage collector for servers · ACM Trans. Program. Lang. Syst. 2005 An efficient parallel heap compaction algorithm · OOPSLA 2004 A Parallel, Incremental and Concurrent GC for Servers · PLDI 2002 |
Runtime systems and virtual machines › garbage collection
concurrent garbage collection |
0.1 | 3 | 2005 | A parallel, incremental, mostly concurrent garbage collector for servers · ACM Trans. Program. Lang. Syst. 2005 Mostly concurrent garbage collection revisited · OOPSLA 2003 A Parallel, Incremental and Concurrent GC for Servers · PLDI 2002 |
Runtime systems and virtual machines
garbage collection |
0.1 | 3 | 2005 | A parallel, incremental, mostly concurrent garbage collector for servers · ACM Trans. Program. Lang. Syst. 2005 Mostly concurrent garbage collection revisited · OOPSLA 2003 A Parallel, Incremental and Concurrent GC for Servers · PLDI 2002 |
Operating systems › resource management
memory management |
0.0 | 1 | 2004 | An efficient parallel heap compaction algorithm · OOPSLA 2004 |
Parallel and multicore computing › multiprocessor system
shared-memory multiprocessor |
0.0 | 1 | 2004 | An efficient parallel heap compaction algorithm · OOPSLA 2004 |
Runtime systems and virtual machines › garbage collection
incremental garbage collection |
0.0 | 1 | 2002 | A Parallel, Incremental and Concurrent GC for Servers · PLDI 2002 |
Methods — techniques the papers use, named apart from their topics
parallel moving strategy · 0.1forwarding pointer · 0.1performance optimization · 0.0work packet mechanism · 0.0memory fence batching · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | A parallel, incremental, mostly concurrent garbage collector for serversabstractMultithreaded applications with multigigabyte heaps running on modern servers provide new challenges for garbage collection (GC). The challenges for “server-oriented” GC include: ensuring short pause times on a multigigabyte heap while minimizing throughput penalty, good scaling on multiprocessor hardware, and keeping the number of expensive multicycle fence instructions required by weak ordering to a minimum.We designed and implemented a collector facing these demands building on the mostly concurrent garbage collector proposed by Boehm et al. [1991]. Our collector incorporates new ideas into the original collector. We make it parallel and incremental; we employ concurrent low-priority background GC threads to take advantage of processor idle time; we propose novel algorithmic improvements to the basic mostly concurrent algorithm improving its efficiency and shortening its pause times; and finally, we use advanced techniques, such as a low-overhead work packet mechanism to enable full parallelism among the incremental and concurrent collecting threads and ensure load balancing.We compared the new collector to the mature, well-optimized, parallel, stop-the-world mark-sweep collector already in the IBM JVM. When allowed to run aggressively, using 72% of the CPU utilization during a short concurrent phase, our collector prototype reduces the maximum pause time from 161 ms to 46 ms while only losing 11.5% throughput when running the SPECjbb2000 benchmark on a 600-MB heap on an 8-way PowerPC 1.1-GHz processors. When the collector is limited to a nonintrusive operation using only 29% of the CPU utilization, the maximum pause time obtained is 79 ms and the loss in throughput is 15.4%. Katherine Barabash, Ori Ben-Yitzhak, Irit Goft, Elliot K. Kolodner, Victor Leikehman, Yoav Ossia, Avi Owshanko, Erez Petrank |
ACM Trans. Program. Lang. Syst. | 6 |
| 2004 | Mostly concurrent compaction for mark-sweep GCabstractA memory manager that does not move objects may suffer from memory fragmentation. Compaction is an efficient, and sometimes inevitable, mechanism for reducing fragmentation. A Mark-Sweep garbage collector must occasionally execute a compaction, usually while the application is suspended. Compaction during pause time can have detrimental effects for interactive applications that require guarantees for maximal pause time. This work presents a method for reducing the pause time created by compaction at a negligible throughput hit. The solution is most suitable when added to a Mark-Sweep garbage collector. Yoav Ossia, Ori Ben-Yitzhak, Marc Segal |
ISMM | 1 |
| 2004 | An efficient parallel heap compaction algorithmabstractWe propose a heap compaction algorithm appropriate for modern computing environments. Our algorithm is targeted at SMP platforms. It demonstrates high scalability when running in parallel but is also extremely efficient when running single-threaded on a uniprocessor. Instead of using the standard forwarding pointer mechanism for updating pointers to moved objects, the algorithm saves information for a pack of objects. It then does a small computation to process this information and determine each object's new location. In addition, using a smart parallel moving strategy, the algorithm achieves (almost) perfect compaction in the lower addresses of the heap, whereas previous algorithms achieved parallelism by compacting within several predetermined segments. Diab Abuaiadh, Yoav Ossia, Erez Petrank, Uri Silbershtein |
OOPSLA | 2 |
| 2003 | Mostly concurrent garbage collection revisitedabstractThe mostly concurrent garbage collection was presented in the seminal paper of Boehm et al. With the deployment of Java as a portable, secure and concurrent programming language, the mostly concurrent garbage collector turned out to be an excellent solution for Java's garbage collection task. The use of this collector is reported for several modern production Java Virtual Machines and it has been investigated further in academia.In this paper, we present a modification of the mostly concurrent collector, which improves the throughput, the memory footprint, and the cache behavior of the collector without foiling the other good qualities (such as short pauses and high scalability). We implemented our solution on the IBM production JVM and obtained a performance improvement of up to 26.7%, a reduction in the heap consumption by up to 13.4%, and no substantial change in the (short) pause times. The modified algorithm was subsequently incorporated into the IBM production JVM. Katherine Barabash, Yoav Ossia, Erez Petrank |
OOPSLA | 2 |
| 2002 | A Parallel, Incremental and Concurrent GC for ServersabstractMultithreaded applications with multi-gigabyte heaps running on modern servers provide new challenges for garbage collection (GC). The challenges for "server-oriented" GC include: ensuring short pause times on a multi-gigabyte heap, while minimizing throughput penalty, good scaling on multiprocessor hardware, and keeping the number of expensive multi-cycle fence instructions required by weak ordering to a minimum. We designed and implemented a fully parallel, incremental, mostly concurrent collector, which employs several novel techniques to meet these challenges. First, it combines incremental GC to ensure short pause times with concurrent low-priority background GC threads to take advantage of processor idle time. Second, it employs a low-overhead work packet mechanism to enable full parallelism among the incremental and concurrent collecting threads and ensure load balancing. Third, it reduces memory fence instructions by using batching techniques: one fence for each block of small objects allocated, one fence for each group of objects marked, and no fence at all in the write barrier. When compared to the mature well-optimized parallel stop-the-world mark-sweep collector already in the IBM JVM, our collector prototype reduces the maximum pause time from 284 ms to 101 ms, and the average pause time from 266 ms to 66 ms while only losing 10% throughput when running the SPECjbb2000 benchmark on a 256 MB heap on a 4-way 550 MHz Pentium multiprocessor. Yoav Ossia, Ori Ben-Yitzhak, Irit Goft, Elliot K. Kolodner, Victor Leikehman, Avi Owshanko |
PLDI | 1 |