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Prabal Sharma

dblp:157/2811 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
—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 · 67% Processor architecture and microarchitecture · 33%

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

TopicWeightPapersLastEvidence papers
Memory systems › cache management › cache interference
cache pollution
0.212014
B-Fetch: Branch Prediction Directed Prefetching for Chip-Multiprocessors · MICRO 2014
Processor architecture and microarchitecture
chip multiprocessor
0.212014
B-Fetch: Branch Prediction Directed Prefetching for Chip-Multiprocessors · MICRO 2014
Memory systems › cache › prefetching
data prefetching
0.212014
B-Fetch: Branch Prediction Directed Prefetching for Chip-Multiprocessors · MICRO 2014

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

cycle-accurate simulation · 0.2
YearPublicationVenuePosition
2014 B-Fetch: Branch Prediction Directed Prefetching for Chip-Multiprocessors
abstract
For decades, the primary tools in alleviating the "Memory Wall" have been large cache hierarchies and dataprefetchers. Both approaches, become more challenging in modern, Chip-multiprocessor (CMP) design. Increasing the last-level cache (LLC) size yields diminishing returns in terms of performance per Watt, given VLSI power scaling trends, this approach becomes hard to justify. These trends also impact hardware budgets for prefetchers. Moreover, in the context of CMPs running multiple concurrent processes, prefetching accuracy is critical to prevent cache pollution effects. These concerns point to the need for a light-weight prefetcher with high accuracy. Existing data prefetchers may generally be classified as low-overhead and low accuracy (Next-n, Stride, etc.) or high-overhead and high accuracy (STeMS, ISB). Wepropose B-Fetch: a data prefetcher driven by branch prediction and effective address value speculation. B-Fetch leverages control flow prediction to generate an expected future path of the executing application. It then speculatively computes the effective address of the load instructions along that path based upon a history of past register transformations. Detailed simulation using a cycle accurate simulator shows a geometric mean speedup of 23.4% for single-threaded workloads, improving to 28.6% for multi-application workloads over a baseline system without prefetching. We find that B-Fetch outperforms an existing "best-of-class" light-weight prefetcher under single-threaded and multi programmed workloads by 9% on average, with 65% less storage overhead.
David Kadjo, Jinchun Kim, Prabal Sharma, Reena Panda, Paul Gratz, Daniel A. Jiménez
MICRO3