Michael Steffen

Stanford University

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Co-Authors

Ronald M. Bonett

University of Tulsa

Joseph Zambreno

Iowa State University

Robin K. Ohls

University of Utah

Shawna Baker

Eunice Kennedy Shriver National Institute of Child Health and Human Development

Jean Lowe

Eunice Kennedy Shriver National Institute of Child Health and Human Development

Sarah Winter

University of Utah

Melody B. Lohmeyer

Duke Regional Hospital

Diane L. Eastman

Eunice Kennedy Shriver National Institute of Child Health and Human Development

Saba Khan Siddiki

Eunice Kennedy Shriver National Institute of Child Health and Human Development

Abhik Das

RTI International

Cooperative Institutions

Eunice Kennedy Shriver National Institute of Child Health and Human Development

548

Research Network (United States)

545

Health and Human Development (2HD) Research Network

301

Clinical Trial Investigators

205

National Institutes of Health

University of Utah

The University of Texas Health Science Center at Houston

The University of Texas Southwestern Medical Center

Nationwide Children's Hospital

Stanford University

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Introducing Graphics Processing from a Systems Perspective: A Hardware/Software Approach

Michael Steffen P. Jones Joseph Zambreno

Abstract Introducing Graphics Processing from a Systems Perspective: A Hardware / Software ApproachTypical courses in computer graphics focus mainly on the core graphics rendering algorithmsand software interfaces – hardware and system-level issues are addressed, if at all, throughclassroom lectures of industrial case studies. We have recently introduced a senior technicalelective which introduces graphics processing from the perspective of the software developer,hardware architect, and system integrator. Towards this end, lecture topics are designed forstudents with no computer graphics background, and focus on solving specific computingproblems using skills learned from a variety of computer engineering courses (e.g. digital logic,computer architecture, software design, embedded systems). As part of the laboratorycomponent, students are presented with a series of bi-weekly design challenges that are gearedtowards implementing a particular module in the 3D graphics pipeline (with both hardware andsoftware support) using an FPGA-based hardware prototyping platform. Although the mainfocus of the labs is on architectural design, hardware implementation, and hardware / softwareverification, each challenge also involves both a functional correctness as well as an optionalperformance optimization component. Only by analyzing the interactions between the graphicsapplication, middleware, architecture, and logic levels can the performance optimization goal beachieved. Each subsequent challenge builds upon those previous, such that by the end of thesemester students will have designed and implemented a fully-functional OpenGL-compliantgraphics processor, capable of running significant applications. The course was introduced in theSpring of 2011 and the results from the final course project indicated that many of our intendedlearning objectives were met; student feedback was also positive.

Graphics hardware

Graphics software

10.18260/1-2--21599

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Examination and Analysis of Implementation Choices within the Material Point Method (MPM)

Computer Modeling in Engineering & Sciences (2008)

Michael Steffen P. C. Wallstedt James E. Guilkey Robert M. Kirby Martin Berzins

The Material Point Method (MPM) has shown itself to be a powerful tool in the sim- ulation of large deformation problems, especially those involving complex geometries and contact where typical finite element type methods fre- quently fail. While these large complex problems lead to some impressive simulations and solu- tions, there has been a lack of basic analysis char- acterizing the errors present in the method, even on the simplest of problems. The large number of choices one has when implementing the method, suchas thechoiceofbasisfunctionsandboundary treatments,furthercomplicates thiserroranalysis. In thispaperweexploresomeofthemany choices one can make when implementing an MPM al- gorithm and the numerical ramifications of these choices. Specifically, we analyze and demonstrate how the smoothing length within the General- ized InterpolationMaterial Point Method (GIMP) can affect the error and stability properties of the method. We also demonstrate how various choices of basis functions and boundary treat- ments affect the spatial convergence properties of MPM.

Smoothing

Material Point Method

Basis (linear algebra)

10.3970/cmes.2008.031.107

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Citations (76)

The Impact of Article 39.3 in India: A Practical Perspective

Vishwas H. Devaiah Tahir Amin Priti Radhakrishnan Michael Steffen

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Citations (1)

Molecular evolution of early insect societies: Genomics of the Australian small carpenter bee,Ceratina australensis

2016 International Congress of Entomology (2016)

Michael Steffen

10.1603/ice.2016.112200

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Developmental Outcomes of Extremely Preterm Infants with a Need for Child Protective Services Supervision

The Journal of Pediatrics (2019)

Elisabeth C. McGowan Abbot R. Laptook Jean Lowe Myriam Peralta‐Carcelen Dhuly Chowdhury

Prenatal Care

Hospital discharge

10.1016/j.jpeds.2019.07.063

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Citations (7)

VizieR Online Data Catalog: 3D correction in 5 photometric systems (Bonifacio+, 2018)

VizieR Online Data Catalog (2018)

P. Bonifacio E. Caffau H.‐G. Ludwig Michael Steffen Francesco Castelli

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Preschool Assessment of Preterm Infants Treated With Darbepoetin and Erythropoietin

PEDIATRICS (2016)

Robin K. Ohls Daniel C. Cannon J. P. Phillips Arvind Caprihan Shrena Patel

We previously reported improved neurodevelopmental outcomes at 2 years among infants treated with the erythropoiesis-stimulating agents (ESAs) darbepoetin alfa (darbepoetin) or erythropoietin. Here we characterize 4-year outcomes.

Darbepoetin alfa

10.1542/peds.2015-3859

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Citations (74)

Design and Evaluation of a Hardware Accelerated Ray Tracing Data Structure.

TPCG (2009)

Michael Steffen Joseph Zambreno

The increase in graphics card performance and processor core count has allowed significant performance acceleration for ray tracing applications. Future graphics architectures are expected to continue increasing the number of processor cores, further improving performance by exploiting data parallelism. However, current ray tracing implementations are based on recursive searches which involve multiple memory reads. Consequently, software implementations are used without any dedicated hardware acceleration. In this paper, we introduce a ray tracing method designed around hierarchical space subdivision schemes that reduces memory operations. In addition, parts of this traversal method can be performed in fixed hardware running in parallel with programmable graphics processors. We used a custom performance simulator that uses our traversal method, based on a kd-tree, to compare against a conventional kd-tree. The system memory requirements and system memory reads are analyzed in detail for both acceleration structures. We simulated six benchmark scenes and show a reduction in the number of memory reads of up to 70 percent compared to current recursive methods for scenes with over 100,000 polygons.

Graphics hardware

Benchmark (surveying)

Tracing

Tree (set theory)

Hardware acceleration

10.2312/localchapterevents/tpcg/tpcg09/101-108

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Citations (2)

A hardware pipeline for accelerating ray traversal algorithms on streaming processors

Michael Steffen Joseph Zambreno

Ray Tracing is a graphics rendering method that uses rays to trace the path of light in a computer model. To accelerate the processing of rays, scenes are typically compiled into smaller spatial boxes using a tree structure and rays then traverse the tree structure to determine relevant spatial boxes. This allows computations involving rays and scene objects to be limited to only objects close to the ray and does not require processing all elements in the computer model. We present a ray traversal pipeline designed to accelerate ray tracing traversal algorithms using a combination of currently used programmable graphics processors and a new fixed hardware pipeline. Our fixed hardware pipeline performs an initial traversal operation that quickly identifies a smaller sized, fixed granularity spatial bounding box from the original scene. This spatial box can then be traversed further to identify subsequently smaller spatial bounding boxes using any user-defined acceleration algorithm. We show that our pipeline allows for an expected level of user programmability, including development of custom data structures, and can support a wide range of processor architectures. The performance of our pipeline is evaluated for ray traversal and intersection stages using a kd-tree ray tracing algorithm and a custom simulator modeling a generic streaming processor architecture. Experimental results show that our pipeline reduces the number of executed instructions on a graphics processor for the traversal operation by 2.15× for visible rays. The memory bandwidth required for traversal is also reduced by a factor of 1.3× for visible rays.

Graphics hardware

Hardware acceleration

10.1109/sasp.2010.5521150

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Citations (4)

New Books

management revue (2009)

Benjamin Balsmeier Durch Managerverschanzung Investitionen Spezifische München Hampp Stefanie Becker

10.5771/0935-9915-2009-3-312

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Citations (0)