Work

An asymmetric distributed shared memory model for heterogeneous parallel systems

Year: 2010

Type: conference-paper

Abstract: Heterogeneous computing combines general purpose CPUs with accelerators to efficiently execute both sequential control-intensive and data-parallel phases of applications. Existing programming models for heterogeneous computing rely on programmers to explicitly manage data transfers between the CPU system memory and accelerator memory.

Source: International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)

DOI: 10.1145/1736020.1736059

Authors: Isaac Gelado, John E. Stone, Javier Cabezas, Sanjay Patel, Nacho Navarro, Wen-mei W. Hwu

Institutions: Universitat Politècnica de Catalunya, University of Illinois Urbana-Champaign

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Semiconductor Research Corporation, Nvidia

OpenAlex ID: W4241790656