EDBT 2026 Demo / reviewers in the wild / expert
Jens Ernst
dblp:51/32
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2006
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-authorSoftware engineering, systems software and programming languages · 1 · 1 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 |
Compilers and program optimization · 50% Runtime systems and virtual machines · 50% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Memory systems · 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 › interpreter
bytecode interpretation |
0.0 | 1 | 1997 | Code Compression · PLDI 1997 |
Compilers and program optimization › code size reduction
code compression |
0.0 | 1 | 1997 | Code Compression · PLDI 1997 |
Memory systems › memory management › virtual memory
paging |
0.0 | 1 | 1997 | Code Compression · PLDI 1997 |
Methods — techniques the papers use, named apart from their topics
wire representation · 0.0interpretation without decompression · 0.0compressed executable representation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | A Distributed, Parallel System for Large-Scale Structure Recognition in Gene Expression Data
Jens Ernst |
HPCC | 1 |
| 1997 | Code CompressionabstractCurrent research in compiler optimization counts mainly CPU time and perhaps the first cache level or two. This view has been important but is becoming myopic, at least from a system-wide viewpoint, as the ratio of network and disk speeds to CPU speeds grows exponentially.For example, we have seen the CPU idle for most of the time during paging, so compressing pages can increase total performance even though the CPU must decompress or interpret the page contents. Another profile shows that many functions are called just once, so reduced paging could pay for their interpretation overhead.This paper describes:• Measurements that show how code compression can save space and total time in some important real-world scenarios.• A compressed executable representation that is roughly the same size as gzipped x86 programs and can be interpreted without decompression. It can also be compiled to high-quality machine code at 2.5 megabytes per second on a 120MHz Pentium processor• A compressed "wire" representation that must be decompressed before execution but is, for example, roughly 21% the size of SPARC code when compressing gcc. Jens Ernst, William S. Evans, Christopher W. Fraser, Steven Lucco, Todd A. Proebsting |
PLDI | 1 |