2000Unpublished venueOpen access

Very low power pipelines using significance compression

Ramón Canal, Antonio González, James E. Smith

Open full text 108 citations

Abstract

Data, addresses, and instructions are compressed by maintaining only significant bytes with two or three extension bits appended to indicate the significant byte positions. This significance compression method is integrated into a 5-stage pipeline, with the extension bits flowing down the pipeline to enable pipeline operations only for the significant bytes. Consequently, register logic and cache activity (and dynamic power) are substantially reduced. An initial trace-driven study shows reduction in activity of approximately 30-40% for each pipeline stage. Several pipeline organizations are studied. A byte serial pipeline is the simplest implementation, but suffers a CPI (cycles per instruction) increase of 79% compared with a conventional 32-bit pipeline. Widening certain pipeline stages in order to balance processing bandwidth leads to an implementation with a CPI 24% higher than the baseline 32-bit design. Finally, full-width pipeline stages with operand gating achieve a CPI within 2-6% of the baseline 32-bit pipeline.

About this research paper

What this paper is about

Data, addresses, and instructions are compressed by maintaining only significant bytes with two or three extension bits appended to indicate the significant byte positions. This significance compression method is integrated into a 5-stage pipeline, with the extension bits flowing down the pipeline to enable pipeline operations only for the significant bytes. Consequently, register logic and cache activity (and dynamic power) are substantially reduced. An initial trace-driven study shows reduction in activity of approximately 30-40% for each pipeline stage. Several pipeline organizations are studied. A byte serial pipeline is the simplest implementation, but suffers a CPI (cycles per instruction) increase of 79% compared with a conventional 32-bit pipeline. Widening certain pipeline stages in order to balance processing bandwidth leads to an implementation with a CPI 24% higher than the baseline 32-bit design. Finally, full-width pipeline stages with operand gating achieve a CPI within 2-6% of the baseline 32-bit pipeline.

Why it matters

OpenAlex reports 108 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Data, addresses, and instructions are compressed by maintaining only significant bytes with two or three extension bits appended to indicate the significant byte positions. This significance compression method is integrated into a 5-stage pipeline, with the extension bits flowing down the pipeline to enable pipeline operations only for the significant bytes. Consequently, register logic and cache activity (and dynamic power) are substantially reduced. An initial trace-driven study shows reduction in activity of approximately 30-40% for each pipeline stage. Several pipeline organizations are studied. A byte serial pipeline is the simplest implementation, but suffers a CPI (cycles per instruction) increase of 79% compared with a conventional 32-bit pipeline. Widening certain pipeline stages in order to balance processing bandwidth leads to an implementation with a CPI 24% higher than the baseline 32-bit design. Finally, full-width pipeline stages with operand gating achieve a CPI within 2-6% of the baseline 32-bit pipeline.

Key concepts: Citation, Computer science, Engineering, Library science

Related papers

Back to paper searchBrowse research topicsOriginal source
Very low power pipelines using significance compression — Research Paper | ScholarLens