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Munish Gupta

dblp:21/6597 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2

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
Energy-efficient computing · 54% Memory systems · 43% Embedded and real-time systems · 3%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems
cache
0.022000
Filtering Memory References to Increase Energy Efficiency · IEEE Trans. Computers 2000
The Filter Cache: An Energy Efficient Memory Structure · MICRO 1997
Energy-efficient computing › memory energy efficiency
low-power cache design
0.022000
Filtering Memory References to Increase Energy Efficiency · IEEE Trans. Computers 2000
The Filter Cache: An Energy Efficient Memory Structure · MICRO 1997
Energy-efficient computing › power management › memory power management
cache energy reduction
0.012000
Filtering Memory References to Increase Energy Efficiency · IEEE Trans. Computers 2000
Memory systems › cache › cache organization
filter cache
0.011997
The Filter Cache: An Energy Efficient Memory Structure · MICRO 1997
Energy-efficient computing
power management
0.011997
The Filter Cache: An Energy Efficient Memory Structure · MICRO 1997
Memory systems › memory hierarchy
cache hierarchy
0.012000
Filtering Memory References to Increase Energy Efficiency · IEEE Trans. Computers 2000
Embedded and real-time systems › embedded software
embedded applications
0.011997
The Filter Cache: An Energy Efficient Memory Structure · MICRO 1997

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

filter cache · 0.0cache reference filtering · 0.0
YearPublicationVenuePosition
2000 Filtering Memory References to Increase Energy Efficiency
abstract
Most modern microprocessors employ one or two levels of on-chip caches in order to improve performance. Caches typically are implemented with static RAM cells and often occupy a large portion of the chip area. Not surprisingly, these caches can consume a significant amount of power. In many applications, such as portable devices, energy efficiency is more important than performance. We propose sacrificing some performance in exchange for energy efficiency by filtering cache references through an unusually small first level cache. We refer to this structure as the filter cache. A second level cache, similar in size and structure to a conventional first level cache, is positioned behind the filter cache and serves to mitigate the performance loss. Extensive experiments indicate that a small filter cache still can achieve a high hit rate and good performance. This approach allows the second level cache to be in a low power mode most of the time, thus resulting in power savings. The filter cache is particularly attractive in low power applications, such as the embedded processors used for communication and multimedia applications. For example, experimental results across a wide range of embedded applications show that a direct mapped 255-byte filter cache achieves a 58 percent power reduction while reducing performance by 21 percent. This trade-off results in a 51 percent reduction in the energy-delay product when compared to a conventional design.
Johnson Kin, Munish Gupta, William H. Mangione-Smith
IEEE Trans. Computers2
1997 The Filter Cache: An Energy Efficient Memory Structure
abstract
Most modern microprocessors employ one or two levels of on-chip caches in order to improve performance. These caches are typically implemented with static RAM cells and often occupy a large portion of the chip area. Not surprisingly, these caches often consume a significant amount of power. In many applications, such as portable devices, low power is more important than performance. We propose to trade performance for power consumption by filtering cache references through an unusually small L1 cache. An L2 cache, which is similar in size and structure to a typical L1 cache, is positioned behind the filter cache and serves to reduce the performance loss. Experimental results across a wide range of embedded applications show that the filter cache results in improved memory system energy efficiency. For example, a direct mapped 256-byte filter cache achieves a 58% power reduction while reducing performance by 21%, corresponding to a 51% reduction in the energy-delay product over conventional design.
Johnson Kin, Munish Gupta, William H. Mangione-Smith
MICRO2