@presentation {yin2022TRANSFORMjulia,
	title = {Julia for Geoscience},
	year = {2022},
	month = {04},
	abstract = {In this tutorial, we will introduce the Julia programming language to the geoscience community, covering topics such as I/O, data processing, inversion, and machine learning. We will begin by installing Julia and relevant packages. Through a series of tutorials, we will demonstrate Julia{\textquoteright}s abstraction power and show how to load and plot data, write your own functions/operators, form and solve a geophysical inverse problem, and demonstrate how to integrate wave-equation solvers in Julia with machine learning frameworks. The intent of this presentation is to provide an introductory level tutorial that will be useful to members of the geoscience community.},
	keywords = {JOLI, JUDI, Julia, machine learning, SLIM, software, TRANSFORM},
	url = {https://transform.softwareunderground.org/2022-julia-for-geoscience},
	url2 = {https://www.youtube.com/watch?v=HyWfp3NzIbg},
	software = {https://github.com/slimgroup/SLIMTutorials},
	author = {Ziyi Yin and Mathias Louboutin and Philipp A. Witte and Ali Siahkoohi and Gabrio Rizzuti and Rafael Orozco and Henryk Modzelewski and Felix J. Herrmann}
}
@presentation {lopez2017SINBADFmci,
	title = {Matrix Completion in Parallel Architectures: Julia Implementation},
	year = {2017},
	publisher = {SINBAD},
	abstract = {Matrix completion techniques offer potential tools for frugal seismic data acquisition, where dense acquisition is replaced by optimization. This shift of focus means that efficient numerical methods are critical for the implementation of these techniques in large-scale seismic applications. To this end, this talk modifies rank-penalization methodologies to suit parallel architectures. By adopting factorization-based alternating minimization schemes, each program can be decoupled into independent sub-problems handled in parallel. We showcase a distributed parallel execution in Julia and explore the scalability of the approach.},
	keywords = {Presentation, SINBAD, SINBADFALL2017, SLIM},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SINBAD/2017/Fall/lopez2017SINBADFmci/lopez2017SINBADFmci.pdf},
	url2 = {https://slim.gatech.edu/Publications/Public/Conferences/SINBAD/2017/Fall/lopez2017SINBADFmci/lopez2017SINBADFmci.mov},
	author = {Oscar Lopez and Keegan Lensink and Rajiv Kumar and Henryk Modzelewski}
}
@presentation {fang2013SINBADsfwi,
	title = {Swift FWI},
	year = {2013},
	publisher = {SINBAD},
	abstract = {In 3D case, there is much more data and modeling is much more expensive. As a result, parallel computing is very important for 3D full-waveform inversion. Both domain decomposition and data decomposition need a large number of parallel computing resources. However, programs based on parallel MATLAB suffer from the limitation of licenses. In order to obtain a MATLAB licenses free solution, we use SWIFT, which is a fast and easy parallel scripting language. Once the original Mat file is complied to an executable file, SWIFT can run the code inside the executable file in parallel without using parallel MATLAB. We use the SWIFT to compute the object functions and gradients of different shots in parallel, and test the parallel 3D FWI code with overthrust data. This is joint work with Thomas Lai, Harsh Juneja, Bas Peters.},
	keywords = {Presentation, SINBAD, SINBADFALL2013, SLIM},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SINBAD/2013/Fall/fang2013SINBADsfwi/fang2013SINBADsfwi.pdf},
	author = {Zhilong Fang and Henryk Modzelewski and Tristan van Leeuwen and Thomas Lai and Harsh Juneja and Bas Peters and Felix J. Herrmann}
}
@presentation {modzelewski2010SINBADsra,
	title = {Software releases and architecture},
	year = {2010},
	publisher = {SINBAD},
	keywords = {Presentation, SINBAD, SINBADFALL2010, SLIM},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SINBAD/2010/Fall/modzelewski2010SINBADsra/modzelewski2010SINBADsra_pres.pdf},
	author = {Henryk Modzelewski}
}
@conference {modzelewski2008SINBADdas,
	title = {Design and specifications for SLIM{\textquoteright}s software framework},
	booktitle = {SINBAD 2008},
	year = {2008},
	abstract = {The SLIM group is actively developing software for seismic imaging. This talk will give a general overview of the software development during SINBAD project with focus on the final release in February 2008. The covered topics will include: 1) adopting Python for object-oriented programming, 2) including parallelism into the algorithms used in seismic imaging/modeling, 3) in-house algorithms for seismic imaging, and 4) contributions to Madagascar (RSF). The talk will serve as an introduction to the other presentations in the session "SINBAD Software releases".},
	keywords = {Presentation, SINBAD, SLIM},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SINBAD/2008/modzelewski2008SINBADdas/modzelewski2008SINBADdas.pdf},
	author = {Henryk Modzelewski}
}
@manual {rossross07MNsda,
	title = {SLIMpy development and programming interface for seismic processing},
	year = {2007},
	abstract = {Inverse problems in (exploration) seismology are known for their large to very large scale. For instance, certain sparsity-promoting inversion techniques involve vectors that easily exceed unknowns while seismic imaging involves the construction and application of matrix-free discretized operators where single matrix-vector evaluations may require hours, days or even weeks on large compute clusters. For these reasons, software development in this field has remained the domain of highly technical codes programmed in low-level languages with little eye for easy development, code reuse and integration with (nonlinear) programs that solve inverse problems.Following ideas from the Symes{\textquoteright} Rice Vector Library and Bartlett{\textquoteright}s C++ object-oriented interface, Thyra, and Reduction/Transformation operators (both part of the Trilinos software package), we developed a software-development environment based on overloading. This environment provides a pathway from in-core prototype development to out-of-core and MPI {\textquoteright}production{\textquoteright} code with a high level of code reuse. This code reuse is accomplished by integrating the out-of-core and MPI functionality into the dynamic object-oriented programming language Python. This integration is implemented through operator overloading and allows for the development of a coordinate-free solver framework that (i) promotes code reuse; (ii) analyses the statements in an abstract syntax tree and (iii) generates executable statements. In the current implementation, we developed an interface to generate executable statements for the out-of-core unix-pipe based (seismic) processing package RSF-Madagascar (rsf.sf.net). The modular design allows for interfaces to other seismic processing packages and to in-core Python packages such as numpy. So far, the implementation overloads linear operators and element-wise reduction/transformation operators. We are planning extensions towards nonlinear operators and integration with existing (parallel) solver frameworks such as Trilinos.},
	keywords = {SLIM, software},
	url = {https://slim.gatech.edu/Software/SLIM/SLIMpy/},
	author = {Sean Ross-Ross and Henryk Modzelewski and Cody R. Brown and Felix J. Herrmann}
}
@conference {modzelewski2006SINBADdas,
	title = {Design and specifications for SLIM{\textquoteright}s software framework},
	booktitle = {SINBAD 2006},
	year = {2006},
	keywords = {Presentation, SINBAD, SLIM},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/SINBAD/2006/modzelewski2006SINBADdas/modzelewski2006SINBADdas.pdf},
	author = {Henryk Modzelewski}
}
