Work

Using Statistical Models for Embedded Java Performance Analysis

Year: 2008

Type: conference-paper

Abstract: —This paper proposes and evaluates rigorous statistical regression techniques for Java performance analysis on a high-end embedded processor (MPC7447A). Our models relate overall Java system performance to various microarchitecture metrics and their interactions. We show that the models we develop in this paper are easy to construct, are interpretable and have high prediction accuracies. I.

Source: Kyushu University Institutional Repository (QIR) (Kyushu University)

Authors: Rao, Pradeep, Murakami, Kazuaki, 村上, 和彰

Institutions: Kyushu University, Institute of Systems, Information Technologies and Nanotechnologies

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Indian Institute of Science

OpenAlex ID: W2288085952

FWCI:

Cites: 11

Cited by:

Related to: 10