Demo Data from EDBT 2026 / reviewers in the wild / expert
Orna Etzion
dblp:55/1842
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 3Software engineering, systems software and programming languages · 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.
| Software engineering, system software, and programming languages
1 paper |
Runtime systems and virtual machines · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Processor architecture and microarchitecture · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Runtime systems and virtual machines
binary translation |
0.0 | 1 | 2003 | IA-32 Execution Layer: a two-phase dynamic translator designed to support IA-32 applications on Itanium-based systems · MICRO 2003 |
Runtime systems and virtual machines › binary translation
dynamic translation |
0.0 | 1 | 2003 | IA-32 Execution Layer: a two-phase dynamic translator designed to support IA-32 applications on Itanium-based systems · MICRO 2003 |
Processor architecture and microarchitecture
instruction set architecture |
0.0 | 1 | 2003 | IA-32 Execution Layer: a two-phase dynamic translator designed to support IA-32 applications on Itanium-based systems · MICRO 2003 |
Methods — techniques the papers use, named apart from their topics
two-phase translation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Module-aware translation for real-life desktop applicationsabstractA dynamic binary translator is a just-in-time compiler that translates source architecture binaries into target architecture binaries on the fly. It enables the fast running of the source architecture binaries on the target architecture. Traditional dynamic binary translators invalidate their translations when a module is unloaded, so later re-loading of the same module will lead to a full retranslation. Moreover, most of the loading and unloading are performed on a few "hot" modules, which causes the dynamic binary translator to spend a significant amount of time on repeatedly translating these "hot" modules. Furthermore, the retranslation may lead to excessive memory consumption if the code pages containing the translated codes that have been invalidated are not timely recycled. In addition, we observed that the overhead for translating real-life desktop applications is a big challenge to the overall performance of the applications, and our detailed analysis proved that real-life desktop applications dynamically load and unload modules much more frequently as compared to popular benchmarks, such as SPEC CPU2000. To address these issues, we propose a translation reuse engine that uses a novel verification method and a module-aware memory management mechanism. The proposed approach was fully implemented in IA-32 Execution Layer (IA-32 EL) [1], a commercial dynamic binary translator that enables the execution of IA-32 applications on Intel® Itanium® processor family. Collected results show that the module-aware translation improves the performance of Adobe* Illustrator by 14.09% and Microsoft* Publisher by 9.73%. The overhead brought by the translation reuse engine accounts for no more than 0.2% of execution time. Orna Etzion |
VEE | 3 |
| 2004 | The Accuracy of Initial Prediction in Two-Phase Dynamic Binary TranslatorsabstractDynamic binary translators use a two-phase approach to identify and optimize frequently executed code dynamically. In the first step (profiling phase), blocks of code are interpreted or quickly translated to collect execution frequency information for the blocks. In the second phase (optimization phase), frequently executed blocks are grouped into regions and advanced optimizations are applied on them. This approach implicitly assumes that the initial profile of each block is representative of the block throughout its lifetime. We investigate the ability of the initial profile to predict the average program behavior. We compare the predicted behavior of varying lengths of the initial execution with the average program behavior for the whole program execution, and use the prediction from the training input as the reference. Our result indicates that, for the SPEC2000 benchmarks, even very short initial profiles have comparable prediction accuracy to the traditional profile-guided optimizations using the training input, although the initial profile is inadequate for predicting loop trip count information for some integer programs and several benchmarks can benefit from phase-awareness during dynamic binary translation. Youfeng Wu, Maurício Breternitz, Justin Quek, Orna Etzion, Jesse Fang |
CGO | 4 |
| 2003 | IA-32 Execution Layer: a two-phase dynamic translator designed to support IA-32 applications on Itanium-based systemsabstractIA-32 execution layer (IA-32 EL) is a new technology that executes IA-32 applications on Intel Itanium processor family systems. Currently, support for IA-32 applications on Itanium-based platforms is achieved using hardware circuitry on the Itanium processors. This capability will be enhanced with IA-32 EL - software that will ship with Itanium-based operating systems and will convert IA-32 instructions into Itanium instructions via dynamic translation. In this paper, we describe aspects of the IA-32 execution layer technology, including the general two-phase translation architecture and the usage of a single translator for multiple operating systems. The paper provides details of some of the technical challenges such as precise exception, emulation of FP, MMX, and Intel streaming SIMD extension instructions, and misalignment handling. Finally, the paper presents some performance results. Leonid Baraz, Tevi Devor, Orna Etzion, Shalom Goldenberg, Alex Skaletsky, Yigel Zemach |
MICRO | 3 |