ICALEPCS2021 - List of Authors (Alnajjar, D.)

Paper	Title	Page
THPV021	TATU: A Flexible FPGA-Based Trigger and Timer Unit Created on CompactRIO for the First Sirius Beamlines	908
	J.R. Piton, D. Alnajjar, D.H.C. Araujo, J.L. Brito Neto, L.P. Do Carmo, L.C. Guedes, M.A.L. Moraes LNLS, Campinas, Brazil
	In the modern synchrotron light sources, the higher brilliance leads to shorter acquisition times at the experimental stations. For most beamlines of the fourth-generation source SIRIUS, it was imperative to shift from the usual software-based synchronization of operations to the much faster triggering by hardware of some key equipment involved in the experiments. As a basis of their control system for devices, the SIRIUS beamlines have standard CompactRIO controllers and I/O modules along the hutches. Equipped with a FPGA and a hard processor running Linux Real-Time, this platform could deal with the triggers from and to other devices, in the order of ms and µs. TATU (Time and Trigger Unit) is a code running in a CompactRIO unit to coordinate multiple triggering conditions and actions. TATU can be either the master pulse generator or the follower of other signals. Complex trigger pattern generation is set from a user-friendly standardized interface. EPICS process variables (by means of LNLS Nheengatu) are used to set parameters and to follow the execution status. The concept and first field test results in at least four SIRIUS beamlines are presented. D. Alnajjar, G. S. Fedel, and J. R. Piton, "Project Nheengatu: EPICS support for CompactRIO FPGA and LabVIEW-RT", ICALEPCS’19, New York, NY, USA, Oct. 2019, paper WEMPL002.
	Poster THPV021 [0.618 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-THPV021
About •	Received ※ 10 October 2021 Accepted ※ 21 November 2021 Issue date ※ 02 February 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

FRBL05	RemoteVis: An Efficient Library for Remote Visualization of Large Volumes Using NVIDIA Index	1047
	T.V. Spina, D. Alnajjar, M.L. Bernardi, F.S. Furusato, E.X. Miqueles, A.Z. Peixinho LNLS, Campinas, Brazil A. Kuhn, M. Nienhaus NVIDIA, Santa Clara, USA
	Funding: We would like to thank the Brazilian Ministry of Science, Technology, and Innovation for the financial support. Advancements in X-ray detector technology are increasing the amount of volumetric data available for material analysis in synchrotron light sources. Such developments are driving the creation of novel solutions to visualize large datasets both during and after image acquisition. Towards this end, we have devised a library called RemoteVis to visualize large volumes remotely in HPC nodes, using NVIDIA IndeX as the rendering backend. RemoteVis relies on RDMA-based data transfer to move large volumes from local HPC servers, possibly connected to X-ray detectors, to remote dedicated nodes containing multiple GPUs for distributed volume rendering. RemoteVis then injects the transferred data into IndeX for rendering. IndeX is a scalable software capable of using multiple nodes and GPUs to render large volumes in full resolution. As such, we have coupled RemoteVis with slurm to dynamically schedule one or multiple HPC nodes to render any given dataset. RemoteVis was written in C/C++ and Python, providing an efficient API that requires only two functions to 1) start remote IndeX instances and 2) render regular volumes and point-cloud (diffraction) data on the web browser/Jupyter client. *NVIDIA IndeX, https://developer.nvidia.com/nvidia-index
	Slides FRBL05 [12.680 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-FRBL05
About •	Received ※ 10 October 2021 Revised ※ 28 October 2021 Accepted ※ 20 November 2021 Issue date ※ 01 March 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

TATU: A Flexible FPGA-Based Trigger and Timer Unit Created on CompactRIO for the First Sirius Beamlines

908

J.R. Piton, D. Alnajjar, D.H.C. Araujo, J.L. Brito Neto, L.P. Do Carmo, L.C. Guedes, M.A.L. Moraes
LNLS, Campinas, Brazil

In the modern synchrotron light sources, the higher brilliance leads to shorter acquisition times at the experimental stations. For most beamlines of the fourth-generation source SIRIUS, it was imperative to shift from the usual software-based synchronization of operations to the much faster triggering by hardware of some key equipment involved in the experiments. As a basis of their control system for devices, the SIRIUS beamlines have standard CompactRIO controllers and I/O modules along the hutches. Equipped with a FPGA and a hard processor running Linux Real-Time, this platform could deal with the triggers from and to other devices, in the order of ms and µs. TATU (Time and Trigger Unit) is a code running in a CompactRIO unit to coordinate multiple triggering conditions and actions. TATU can be either the master pulse generator or the follower of other signals. Complex trigger pattern generation is set from a user-friendly standardized interface. EPICS process variables (by means of LNLS Nheengatu*) are used to set parameters and to follow the execution status. The concept and first field test results in at least four SIRIUS beamlines are presented.
* D. Alnajjar, G. S. Fedel, and J. R. Piton, "Project Nheengatu: EPICS support for CompactRIO FPGA and LabVIEW-RT", ICALEPCS’19, New York, NY, USA, Oct. 2019, paper WEMPL002.

Poster THPV021 [0.618 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-THPV021

About •

Received ※ 10 October 2021 Accepted ※ 21 November 2021 Issue date ※ 02 February 2022

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

FRBL05

RemoteVis: An Efficient Library for Remote Visualization of Large Volumes Using NVIDIA Index

1047

T.V. Spina, D. Alnajjar, M.L. Bernardi, F.S. Furusato, E.X. Miqueles, A.Z. Peixinho
LNLS, Campinas, Brazil
A. Kuhn, M. Nienhaus
NVIDIA, Santa Clara, USA

Funding: We would like to thank the Brazilian Ministry of Science, Technology, and Innovation for the financial support.
Advancements in X-ray detector technology are increasing the amount of volumetric data available for material analysis in synchrotron light sources. Such developments are driving the creation of novel solutions to visualize large datasets both during and after image acquisition. Towards this end, we have devised a library called RemoteVis to visualize large volumes remotely in HPC nodes, using NVIDIA IndeX as the rendering backend. RemoteVis relies on RDMA-based data transfer to move large volumes from local HPC servers, possibly connected to X-ray detectors, to remote dedicated nodes containing multiple GPUs for distributed volume rendering. RemoteVis then injects the transferred data into IndeX for rendering. IndeX is a scalable software capable of using multiple nodes and GPUs to render large volumes in full resolution. As such, we have coupled RemoteVis with slurm to dynamically schedule one or multiple HPC nodes to render any given dataset. RemoteVis was written in C/C++ and Python, providing an efficient API that requires only two functions to 1) start remote IndeX instances and 2) render regular volumes and point-cloud (diffraction) data on the web browser/Jupyter client.
*NVIDIA IndeX, https://developer.nvidia.com/nvidia-index

Slides FRBL05 [12.680 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-FRBL05

About •

Received ※ 10 October 2021 Revised ※ 28 October 2021 Accepted ※ 20 November 2021 Issue date ※ 01 March 2022

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)