TY - GEN
T1 - High performance molecular visualization
T2 - 30th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2016
AU - Stone, John E.
AU - Messmer, Peter
AU - Sisneros, Robert
AU - Schulten, Klaus
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/18
Y1 - 2016/7/18
N2 - Large scale molecular dynamics simulations produce terabytes of data that is impractical to transfer to remote facilities. It is therefore necessary to perform visualization tasks in-situ as the data are generated, or by running interactive remote visualization sessions and batch analyses co-located with direct access to high performance storage systems. A significant challenge for deploying visualization software within clouds, clusters, and supercomputers involves the operating system software required to initialize and manage graphics acceleration hardware. Recently, it has become possible for applications to use the Embedded-system Graphics Library (EGL) to eliminate the requirement for windowing system software on compute nodes, thereby eliminating a significant obstacle to broader use of high performance visualization applications. We outline the potential benefits of this approach in the context of visualization applications used in the cloud, on commodity clusters, and supercomputers. We discuss the implementation of EGL support in VMD, a widely used molecular visualization application, and we outline benefits of the approach for molecular visualization tasks on petascale computers, clouds, and remote visualization servers. We then provide a brief evaluation of the use of EGL in VMD, with tests using developmental graphics drivers on conventional workstations and on Amazon EC2 G2 GPU-accelerated cloud instance types. We expect that the techniques described here will be of broad benefit to many other visualization applications.
AB - Large scale molecular dynamics simulations produce terabytes of data that is impractical to transfer to remote facilities. It is therefore necessary to perform visualization tasks in-situ as the data are generated, or by running interactive remote visualization sessions and batch analyses co-located with direct access to high performance storage systems. A significant challenge for deploying visualization software within clouds, clusters, and supercomputers involves the operating system software required to initialize and manage graphics acceleration hardware. Recently, it has become possible for applications to use the Embedded-system Graphics Library (EGL) to eliminate the requirement for windowing system software on compute nodes, thereby eliminating a significant obstacle to broader use of high performance visualization applications. We outline the potential benefits of this approach in the context of visualization applications used in the cloud, on commodity clusters, and supercomputers. We discuss the implementation of EGL support in VMD, a widely used molecular visualization application, and we outline benefits of the approach for molecular visualization tasks on petascale computers, clouds, and remote visualization servers. We then provide a brief evaluation of the use of EGL in VMD, with tests using developmental graphics drivers on conventional workstations and on Amazon EC2 G2 GPU-accelerated cloud instance types. We expect that the techniques described here will be of broad benefit to many other visualization applications.
KW - In-situ visualization
KW - Molecular visualization
KW - Parallel rendering
KW - Remote visualization
UR - http://www.scopus.com/inward/record.url?scp=84991633863&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84991633863&partnerID=8YFLogxK
U2 - 10.1109/IPDPSW.2016.127
DO - 10.1109/IPDPSW.2016.127
M3 - Conference contribution
AN - SCOPUS:84991633863
T3 - Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
SP - 1014
EP - 1023
BT - Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 23 May 2016 through 27 May 2016
ER -