Demo Data from EDBT 2026 / reviewers in the wild / expert
Brian Slechta
dblp:99/3339
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 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.
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Processor architecture and microarchitecture · 100% |
Topics — the 4 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Processor architecture and microarchitecture
instruction-level parallelism |
0.0 | 1 | 2003 | Dynamic Optimization of Micro-Operations · HPCA 2003 |
Processor architecture and microarchitecture
dynamic optimization |
0.0 | 1 | 2001 | Performance characterization of a hardware mechanism for dynamic optimization · MICRO 2001 |
Processor architecture and microarchitecture › instruction set architecture › CISC
x86 |
0.0 | 1 | 2003 | Dynamic Optimization of Micro-Operations · HPCA 2003 |
Processor architecture and microarchitecture
superscalar processor |
0.0 | 1 | 2001 | Performance characterization of a hardware mechanism for dynamic optimization · MICRO 2001 |
Methods — techniques the papers use, named apart from their topics
trace-driven simulation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Dynamic Optimization of Micro-OperationsabstractInherent within complex instruction set architectures such as /spl times/86 are inefficiencies that do not exist in a simpler ISA. Modern /spl times/86 implementations decode instructions into one or more micro-operations in order to deal with the complexity of the ISA. Since these micro-operations are not visible to the compiler the stream of micro-operations can contain redundancies even in statically optimized /spl times/86 code. Within a processor implementation, however barriers at the ISA level do not apply, and these redundancies can be removed by optimizing the micro-operation stream. In this paper we explore the opportunities to optimize code at the micro-operation granularity. We execute these micro-operation optimizations using the rePLay Framework as a microarchitectural substrate. Using a simple set of seven optimizations, including two that aggressively and speculatively attempt to remove redundant load instructions, we examine the effects of dynamic optimization of micro-operations using a trace-driven simulation environment. Simulation reveals that across a sampling of SPECint 2000 and real /spl times/86 applications, rePLay is able to reduce micro-operation count by 21% and, in particular load micro-operation count by 22%. These reductions correspond to a boost in observed instruction-level parallelism on an 8-wide optimizing rePLay processor by 17% over a non-optimizing configuration. Brian Slechta, David Crowe, Brian Fahs, Michael Fertig, Gregory A. Muthler, Justin Quek, Francesco Spadini, Sanjay J. Patel, Steven S. Lumetta |
HPCA | 1 |
| 2001 | Performance characterization of a hardware mechanism for dynamic optimizationabstractWe evaluate the rePLay microarchitecture as a means for reducing application execution time by facilitating dynamic optimization. The framework contains a programmable optimization engine coupled with a hardware-based recovery mechanism. The optimization engine enables the dynamic optimizer to run concurrently with program execution. The recovery mechanism enables the optimizer to make speculative optimizations without requiring recovery code. We demonstrate that a rePLay configuration performing a small suite of simple optimizations on Alpha code attains an average of 13% reduction in execution cycles on the SPEC2000 integer benchmarks over a rePLay configuration not performing optimizations, and a 21% reduction over an aggressive standard superscalar microarchitecture. Brian Fahs, Satarupa Bose, Matthew M. Crum, Brian Slechta, Francesco Spadini, Tony Tung, Sanjay J. Patel, Steven S. Lumetta |
MICRO | 4 |