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Todd M. Rafacz

dblp:01/722 · DBLP profile ↗
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2ranked-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 · 2Security and privacy · 1Software 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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Processor architecture and microarchitecture · 100%
Software engineering, system software, and programming languages
1 paper
Compilers and program optimization · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Processor architecture and microarchitecture
dynamic optimization
0.112005
Continuous Optimization · ISCA 2005
Compilers and program optimization › compiler optimization
dataflow optimization
0.012005
Continuous Optimization · ISCA 2005

Methods — techniques the papers use, named apart from their topics

store forwarding · 0.1redundant load elimination · 0.1reassociation · 0.1constant propagation · 0.1
YearPublicationVenuePosition
2005 Continuous Optimization
abstract
This paper presents a hardware-based dynamic optimizer that continuously optimizes an application's instruction stream. In continuous optimization, dataflow optimizations are performed using simple, table-based hardware placed in the rename stage of the processor pipeline. The continuous optimizer reduces dataflow height by performing constant propagation, reassociation, redundant load elimination, store forwarding, and silent store removal. To enhance the impact of the optimizations, the optimizer integrates values generated by the execution units back into the optimization process. Continuous optimization allows instructions with input values known at optimization time to be executed in the optimizer, leaving less work for the out-of-order portion of the pipeline. Continuous optimization can detect branch mispredictions earlier and thus reduce the misprediction penalty. In this paper, we present a detailed description of a hardware optimizer and evaluate it in the context of a contemporary microarchitecture running current workloads. Our analysis of SPECint, SPECfp, and mediabench workloads reveals that a hardware optimizer can directly execute 33% of instructions, resolve 29% of mispredicted branches, and generate addresses for 76% of memory operations. These positive effects combine to provide speed ups in the range 0.99 to 1.27.
Brian Fahs, Todd M. Rafacz, Sanjay J. Patel, Steven S. Lumetta
ISCA2
2004 Characterizing the Effects of Transient Faults on a High-Performance Processor Pipeline
abstract
The progression of implementation technologies into the sub-100 nanometer lithographies renew the importance of understanding and protecting against single-event upsets in digital systems. In this work, the effects of transient faults on high performance microprocessors is explored. To perform a thorough exploration, a highly detailed register transfer level model of a deeply pipelined, out-of-order microprocessor was created. Using fault injection, we determined that fewer than 15% of single bit corruptions in processor state result in software visible errors. These failures were analyzed to identify the most vulnerable portions of the processor, which were then protected using simple low-overhead techniques. This resulted in a 75% reduction in failures. Building upon the failure modes seen in the microarchitecture, fault injections into software were performed to investigate the level of masking that the software layer provides. Together, the baseline microarchitectural substrate and software mask more than 9 out of 10 transient faults from affecting correct program execution.
Nicholas J. Wang, Justin Quek, Todd M. Rafacz, Sanjay J. Patel
DSN3