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Record W3023407106 · doi:10.1145/384264.379242

OS and compiler considerations in the design of the IA-64 architecture

2000· article· en· W3023407106 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACM SIGOPS Operating Systems Review · 2000
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsHewlett-Packard (Canada)
Fundersnot available
KeywordsComputer scienceCompilerInstruction-level parallelismInstruction setExploitComputer architectureParallelism (grammar)ArchitectureAddressing modeProcessor registerPaceParallel computingOperating systemInstructions per cycleMemory address

Abstract

fetched live from OpenAlex

Increasing demands for processor performance have outstripped the pace of process and frequency improvements, pushing designers to find ways of increasing the amount of work that can be processed in parallel. Traditional RISC architectures use hardware approaches to obtain more instruction-level parallelism, with the compiler and the operating system (OS) having only indirect visibility into the mechanisms used.The IA-64 architecture [14] was specifically designed to enable systems which create and exploit high levels of instruction-level parallelism by explicitly encoding a program's parallelism in the instruction set [25]. This paper provides a qualitative summary of the IA-64 architecture features that support control and data speculation, and register stacking. The paper focusses on the functional synergy between these architectural elements (rather than their individual performance merits), and emphasizes how they were designed for cooperation between processor hardware, compilers and the OS.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.292
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it