ICALEPCS2011 - List of Authors (Shen, G.)

Paper

Title

Page

EPICS V4 in Python

830

G. Shen, M.A. Davidsaver, M.R. Kraimer
BNL, Upton, Long Island, New York, USA

Funding: Work supported under auspices of the U.S. Department of Energy under Contract No. DE-AC02-98CH10886 with Brookhaven Science Associates, LLC, and in part by the DOE Contract DE-AC02-76SF00515
A novel design and implementation of EPICS version 4 is undergoing in Python. EPICS V4 defined an efficient way to describe a complex data structure, and data protocol. Current implementation in either C++ or Java has to invent a new wheel to present its data structure. However, it is more efficient in Python by mapping the data structure into a numpy array. This presentation shows the performance benchmarking, comparison in different language, and current status.

FRBHMULT06

EPICS V4 Expands Support to Physics Application, Data Acsuisition, and Data Analysis

1338

L.R. Dalesio, G. Carcassi, M.A. Davidsaver, M.R. Kraimer, R. Lange, N. Malitsky, G. Shen
BNL, Upton, Long Island, New York, USA
T. Korhonen
Paul Scherrer Institut, 5232 Villigen PSI, Switzerland
J. Rowland
Diamond, Oxfordshire, United Kingdom
M. Sekoranja
Cosylab, Ljubljana, Slovenia
G.R. White
SLAC, Menlo Park, California, USA

Funding: Work supported under auspices of the U.S. Department of Energy under Contract No. DE-AC02-98CH10886 with Brookhaven Science Associates, LLC, and in part by the DOE Contract DE-AC02-76SF00515
EPICS version 4 extends the functionality of version 3 by providing the ability to define, transport, and introspect composite data types. Version 3 provided a set of process variables and a data protocol that adequately defined scalar data along with an atomic set of attributes. While remaining backward compatible, Version 4 is able to easily expand this set with a data protocol capable of exchanging complex data types and parameterized data requests. Additionally, a group of engineers defined reference types for some applications in this environment. The goal of this work is to define a narrow interface with the minimal set of data types needed to support a distributed architecture for physics applications, data acquisition, and data analysis.

Slides FRBHMULT06 [0.188 MB]

Paper	Title	Page
WEPKS021	EPICS V4 in Python	830
	G. Shen, M.A. Davidsaver, M.R. Kraimer BNL, Upton, Long Island, New York, USA
	Funding: Work supported under auspices of the U.S. Department of Energy under Contract No. DE-AC02-98CH10886 with Brookhaven Science Associates, LLC, and in part by the DOE Contract DE-AC02-76SF00515 A novel design and implementation of EPICS version 4 is undergoing in Python. EPICS V4 defined an efficient way to describe a complex data structure, and data protocol. Current implementation in either C++ or Java has to invent a new wheel to present its data structure. However, it is more efficient in Python by mapping the data structure into a numpy array. This presentation shows the performance benchmarking, comparison in different language, and current status.

FRBHMULT06	EPICS V4 Expands Support to Physics Application, Data Acsuisition, and Data Analysis	1338
	L.R. Dalesio, G. Carcassi, M.A. Davidsaver, M.R. Kraimer, R. Lange, N. Malitsky, G. Shen BNL, Upton, Long Island, New York, USA T. Korhonen Paul Scherrer Institut, 5232 Villigen PSI, Switzerland J. Rowland Diamond, Oxfordshire, United Kingdom M. Sekoranja Cosylab, Ljubljana, Slovenia G.R. White SLAC, Menlo Park, California, USA
	Funding: Work supported under auspices of the U.S. Department of Energy under Contract No. DE-AC02-98CH10886 with Brookhaven Science Associates, LLC, and in part by the DOE Contract DE-AC02-76SF00515 EPICS version 4 extends the functionality of version 3 by providing the ability to define, transport, and introspect composite data types. Version 3 provided a set of process variables and a data protocol that adequately defined scalar data along with an atomic set of attributes. While remaining backward compatible, Version 4 is able to easily expand this set with a data protocol capable of exchanging complex data types and parameterized data requests. Additionally, a group of engineers defined reference types for some applications in this environment. The goal of this work is to define a narrow interface with the minimal set of data types needed to support a distributed architecture for physics applications, data acquisition, and data analysis.
	Slides FRBHMULT06 [0.188 MB]