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Sahil Koladiya

dblp:173/9811 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

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

Systems, architecture and hardware · 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
Memory systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems
cache
0.212015
Efficiently prefetching complex address patterns · MICRO 2015
Memory systems › cache › prefetching
data prefetching
0.212015
Efficiently prefetching complex address patterns · MICRO 2015
Memory systems
cache miss prediction
0.112015
Efficiently prefetching complex address patterns · MICRO 2015

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

variable length delta history · 0.2multiple prediction tables · 0.2
YearPublicationVenuePosition
2015 Efficiently prefetching complex address patterns
abstract
Prior work in hardware prefetching has focused mostly on either predicting regular streams with uniform strides, or predicting irregular access patterns at the cost of large hardware structures. This paper introduces the Variable Length Delta Prefetcher (VLDP), which builds up delta histories between successive cache line misses within physical pages, and then uses these histories to predict the order of cache line misses in new pages. One of VLDP's distinguishing features is its use of multiple prediction tables, each of which stores predictions based on a different length of input history. For example, the first prediction table takes as input only the single most recent delta between cache misses within a page, and attempts to predict the next cache miss in that page. The second prediction table takes as input a sequence of the two most recent deltas between cache misses within a page, and also attempts to predict the next cache miss in that page, and so on with additional tables. Longer histories generally yield more accurate predictions, so VLDP prefers to make predictions based on the longest history table that has a matching entry.
Manjunath Shevgoor, Sahil Koladiya, Rajeev Balasubramonian, Chris Wilkerson, Seth H. Pugsley, Zeshan Chishti
MICRO2