{"id":1131,"date":"2011-11-24T10:34:16","date_gmt":"2011-11-24T09:34:16","guid":{"rendered":"http:\/\/viscomp.alexandra.dk\/?p=1131"},"modified":"2011-11-24T10:34:16","modified_gmt":"2011-11-24T09:34:16","slug":"accelerating-computations-a-research-conference-on-graphics-processing-units-visual-computing-and-beyond","status":"publish","type":"post","link":"https:\/\/viscomp.alexandra.dk\/?p=1131","title":{"rendered":"Accelerating Computations – a research conference on graphics processing units, visual computing and beyond"},"content":{"rendered":"

Welcome to a day with talks on Accelerating Computations. <\/em><\/p>\n

On 15 December 2011 the Computer Graphics Lab at the Alexandra Institute in Aarhus will host a conference on the core aspects of accelerating computations. This research conference will be divided into a technical part called Technical Talks in the morning and a business-oriented part called Applications Talks in the afternoon.<\/p>\n

The conference is free and you can participate either in the Technical Talks, the Applications Talks or both. Keynote speaker will be David McAllister from NVIDIA.<\/p>\n

The Computer Graphics Lab at the Alexandra Institute is working on realising efficient computations on massive data sets by using modern many-core processors and massive data algorithms. Subsequently
\ninteractive information visualisation is crucial to analyse and understand massive data sets.<\/p>\n

PROGRAMME<\/h2>\n

10:00- 10:15<\/em> Introduction<\/strong><\/p>\n

10:15 \u2013 14:45<\/em> Technical Talks<\/h3>\n

10:15 \u2013 11:00<\/em> How OptiX Makes the GPU Shine \u2013 a look inside NVIDIA\u2019s Ray Tracing Engine<\/strong>, David McAllister, NVIDIA
\n11:00 \u2013 11:45<\/em> MR reconstruction on GPU<\/strong>, Thomas Sangild, Computer Science, Aarhus University
\n11:45 \u2013 12:30<\/em> Lunch
\n12:30- 13:15<\/em> Parthenon Renderer Revealed<\/strong>, Toshiya Hachisuka, Computer Science, Aarhus University
\n13:15- 13:45<\/em> Subsurface Light Propagation Volumes<\/strong>, Thomas Kim Kjeldsen, Computer Graphics Lab, Alexandra Institute
\n13:45 \u2013 14:00<\/em> Coffee break
\n14:00 \u2013 14:45<\/em> Accelerating Dense Linear Algebra on the GPU<\/strong>, Hans Henrik Brandenborg S\u00f8rensen, DTU Informatics<\/p>\n

14:45 \u2013 16:45<\/em> Applications Talks<\/h3>\n

14:45 \u2013 15:15<\/em> Massive acceleration<\/strong>, Jesper Mosegaard, Computer Graphics Lab, Alexandra Institute
\n15:15 – 15:30<\/em> Coffee break
\n15:30 \u2013 16:15<\/em> Dozens of Uses for Billions of Rays \u2013 a survey of ray tracing applications<\/strong>, David McAllister, NVIDIA
\n16:15 \u2013 16:45 Scalable GPU computing service architecture: LEGO 3DServices<\/strong>, Henrik H\u00f8j Madsen, LEGO, Michael Sch\u00f8ler, Hinnerup.net.<\/p>\n

16:45 \u2013 Networking and sandwiches<\/strong><\/p>\n

Venue: <\/em><\/strong>Alexandra Institute, Peter B\u00f8gh Andersen Auditorium, building 5335, Finlandsgade 21-23, 8200 Aarhus N, Denmark<\/p>\n

Registration:<\/em><\/strong> Online at http:\/\/viscomp.alexandra.dk\/signup\/
\nno later than 12 December <\/em><\/p>\n

Abstracts<\/em><\/h1>\n

How OptiX Makes the GPU Shine \u2013 a look inside NVIDIA\u2019s Ray Tracing Engine<\/h2>\n

David McAllister, Optix Manager, NVIDIA<\/em><\/p>\n

I will briefly describe the OptiX programming model, then dive into the internals of how we exposed the
\nGPU\u2019s computational power for ray tracing in an application programmable way.<\/p>\n

MR reconstruction on GPU<\/h2>\n

Thomas Sangild S\u00f8rensen, Associate Professor, Computer Science, Aarhus University<\/em><\/p>\n

A barrier to the adoption of non-Cartesian parallel magnetic resonance imaging for real-time applications has been the times required for the image reconstructions. These times have exceeded the underlying acquisition time thus preventing real-time display of the acquired images. We present a reconstruction algorithm for commodity graphics hardware (GPUs) to enable real time reconstruction of sensitivity encoded radial imaging (radial SENSE).<\/p>\n

Parthenon Renderer Revealed<\/h2>\n

Toshiya Hachisuka, Assistant Professor, Computer Science, Aarhus University<\/em><\/p>\n

Parthenon Renderer, initially released back in 2002, is one of the earliest publicly available rendering software that utilise graphics hardware for accelerating computation of high-quality offline rendering. I will talk about the inside of Parthenon Renderer in order to give you some examples of engineering choices and algorithm design that make (and made) sense for an offline rendering system using graphics hardware.<\/p>\n

Subsurface Light Propagation Volumes<\/h2>\n

Thomas Kim Kjeldsen, Research and Innovation Scientist, Computer Graphics Lab, Alexandra Institute<\/em><\/p>\n

We present the Subsurface Light Propagation Volume (SSLPV) method for real-time approximation of
\nsubsurface scattering effects in dynamic scenes with changing mesh topology and lighting. SSLPV extends
\nthe Light Propagation Volume (LPV) technique for indirect illumination in video games. We introduce a
\nnew consistent method for injecting flux from point light sources into an LPV grid, a new rendering method
\nwhich consistently converts light intensity stored in an LPV grid into incident radiance, as well as a model for
\nlight scattering and absorption inside heterogeneous materials. Our scheme does not require any precomputation
\nand handles arbitrarily deforming meshes. We show that SSLPV provides visually pleasing results
\nin real-time at the expense of a few milliseconds of added rendering time.<\/p>\n

Accelerating Dense Linear Algebra on the GPU<\/h2>\n

Hans Henrik Brandenborg S\u00f8rensen, Post. Doc., GPU Lab, DTU Informatics<\/em><\/p>\n

GPUs have already become an integral part of high performance scientific computing, since they offer
\ndedicated parallel hardware that can potentially accelerate the execution of many scientific applications.
\nIn this talk, I will consider the automatic performance acceleration of dense vector and matrix-vector operations
\non GPUs. Such operations form the backbone of level 1 and level 2 routines in the Basic Linear Algebra
\nSubroutines (BLAS) library and are therefore of great importance in many scientific applications. The target
\nhardware is the most recent NVIDIA Tesla 20-series (Fermi architecture). Most of the techniques I discuss
\nfor accelerating dense linear algebra are applicable to memory-bound GPU algorithms in general.<\/p>\n

Massive Acceleration at the Alexandra CG Lab<\/h2>\n

Jesper Bjerg Mosegaard, Head of Research and Innovation, Computer Graphics Lab, Alexandra Institute<\/em><\/p>\n

The Computer Graphics Lab at the Alexandra Institute does research and development within the topic of
\nfast and accurate simulation and visualisation in high quality. This talk describes the role of the Alexandra
\nInstitute in transferring research to application in Danish Industry as well as specific opportunities for
\ncompanies to benefit from the latest knowledge and technology.<\/p>\n

Dozens of Uses for Billions of Rays \u2013 a survey of ray tracing applications<\/h2>\n

David McAllister, Optix Manager, NVIDIA<\/em><\/p>\n

Since introducing OptiX in 2009, NVIDIA has been approached by engineers from industries as diverse as
\ngeothermal exploration, cell phone antenna design, and automotive headlamp design that have one thing
\nin common \u2013 the need to intersect rays, usually billions of them, against a database of geometry. I will
\nsurvey many applications of ray tracing, within and beyond computer graphics, and show how accelerating
\nray tracing using GPUs addresses many challenges in industry.<\/p>\n

Scalable GPU computing service architecture: LEGO 3DServices<\/h2>\n

Michael Sch\u00f8ler, Hinnerup.net og Henrik H\u00f8j Madsen, Solution Architect, Lego<\/em><\/p>\n

As LEGO is moving into the virtual playspace, a platform technology has been developed in-house primarily
\nbased on NVIDIA technologies, featuring:<\/p>\n

\u2022 CUDA, OptiX, OpenGL and general shaders
\n\u2022 17 Quadro Plex in multiple environments, multiple datacentres
\n\u2022 Advanced shading techniques for approaching high-quality results in real-time
\n\u2022 On-demand asset generation
\n\u2022 CDN assets distribution
\n\u2022 A generic service-oriented interface
\n\u2022 A distributed rendering architecture
\n\u2022 Architectural patterns for distributed computing
\n\u2022 A plugin architecture supporting existing and future LEGO experiences
\n\u2022 A mentality shift from traditional ways of doing things on CPU vs GPU.
\n\u2022 General experiences from developing on NVIDIA tech in a large-scale Enterprise setup<\/p>\n

The LEGO 3DServices system is designed to support diverse computational needs such as on-demand rendering, mesh optimisation, a Massive Multiplayer Online Game (MMO), product visualisations, 3D modeling and other current and future demanding computational tasks. Our aim with this session is to share our learnings and present LEGO\u2019s vision of the future of distributed GPU accelerated computation as a business-driven platform technology.<\/p>\n","protected":false},"excerpt":{"rendered":"

Welcome to a day with talks on Accelerating Computations. On 15 December 2011 the Computer Graphics Lab at the Alexandra Institute in Aarhus will host a conference on the core aspects of accelerating computations. This research conference will be divided into a technical part called Technical Talks in the morning and a business-oriented part called Applications Talks in the afternoon. The conference is free and you can participate either in the Technical Talks, the Applications Talks or both. Keynote speaker will be David McAllister from NVIDIA. The Computer Graphics Lab at the Alexandra Institute is working on realising efficient computations on massive data sets by using modern many-core processors and massive data algorithms. Subsequently interactive information visualisation is crucial to analyse and understand massive data sets. PROGRAMME 10:00- 10:15 Introduction 10:15 \u2013 14:45 Technical Talks 10:15 \u2013 11:00 How OptiX Makes the GPU Shine \u2013 a look inside NVIDIA\u2019s Ray Tracing Engine, David McAllister, NVIDIA 11:00 \u2013 11:45 MR reconstruction on GPU, Thomas Sangild, Computer Science, Aarhus University 11:45 \u2013 12:30 Lunch 12:30- 13:15 Parthenon Renderer Revealed, Toshiya Hachisuka, Computer Science, Aarhus University 13:15- 13:45 Subsurface Light Propagation Volumes, Thomas Kim Kjeldsen, Computer Graphics Lab, Alexandra Institute 13:45 \u2013 14:00 Coffee break 14:00 \u2013 14:45 Accelerating Dense Linear Algebra on the GPU, Hans Henrik Brandenborg S\u00f8rensen, DTU Informatics 14:45 \u2013 16:45 Applications Talks 14:45 \u2013 15:15 Massive acceleration, Jesper Mosegaard, Computer Graphics Lab, Alexandra Institute 15:15 – 15:30 Coffee break 15:30 \u2013 16:15 Dozens of Uses for Billions of Rays \u2013 a survey of ray tracing applications, David McAllister, NVIDIA 16:15 \u2013 16:45 Scalable GPU computing service architecture: LEGO 3DServices, Henrik H\u00f8j Madsen, LEGO, Michael Sch\u00f8ler, Hinnerup.net. 16:45 \u2013 Networking and sandwiches Venue: Alexandra Institute, Peter B\u00f8gh Andersen Auditorium, building 5335, Finlandsgade 21-23, 8200 Aarhus N, Denmark Registration: Online at http:\/\/viscomp.alexandra.dk\/signup\/ no later than 12 December Abstracts How OptiX Makes the GPU Shine \u2013 a look inside NVIDIA\u2019s Ray Tracing Engine David McAllister, Optix Manager, NVIDIA I will briefly describe the OptiX programming model, then dive into the internals of how we exposed the GPU\u2019s computational power for ray tracing in an application programmable way. MR reconstruction on GPU Thomas Sangild S\u00f8rensen, Associate Professor, Computer Science, Aarhus University A barrier to the adoption of non-Cartesian parallel magnetic resonance imaging for real-time applications has been the times required for the image reconstructions. These times have exceeded the underlying acquisition time thus preventing real-time display of the acquired images. We present a reconstruction algorithm for commodity graphics hardware (GPUs) to enable real time reconstruction of sensitivity encoded radial imaging (radial SENSE). Parthenon Renderer Revealed Toshiya Hachisuka, Assistant Professor, Computer Science, Aarhus University Parthenon Renderer, initially released back in 2002, is one of the earliest publicly available rendering software that utilise graphics hardware for accelerating computation of high-quality offline rendering. I will talk about the inside of Parthenon Renderer in order to give you some examples of engineering choices and algorithm design that make (and made) sense for an offline rendering system using graphics hardware. Subsurface Light Propagation Volumes Thomas Kim Kjeldsen, Research and Innovation Scientist, Computer Graphics Lab, Alexandra Institute We present the Subsurface Light Propagation Volume (SSLPV) method for real-time approximation of subsurface scattering effects in dynamic scenes with changing mesh topology and lighting. SSLPV extends the Light Propagation Volume (LPV) technique for indirect illumination in video games. We introduce a new consistent method for injecting flux from point light sources into an LPV grid, a new rendering method which consistently converts light intensity stored in an LPV grid into incident radiance, as well as a model for light scattering and absorption inside heterogeneous materials. Our scheme does not require any precomputation and handles arbitrarily deforming meshes. We show that SSLPV provides visually pleasing results in real-time at the expense of a few milliseconds of added rendering time. Accelerating Dense Linear Algebra on the GPU Hans Henrik Brandenborg S\u00f8rensen, Post. Doc., GPU Lab, DTU Informatics GPUs have already become an integral part of high performance scientific computing, since they offer dedicated parallel hardware that can potentially accelerate the execution of many scientific applications. In this talk, I will consider the automatic performance acceleration of dense vector and matrix-vector operations on GPUs. Such operations form the backbone of level 1 and level 2 routines in the Basic Linear Algebra Subroutines (BLAS) library and are therefore of great importance in many scientific applications. The target hardware is the most recent NVIDIA Tesla 20-series (Fermi architecture). Most of the techniques I discuss for accelerating dense linear algebra are applicable to memory-bound GPU algorithms in general. Massive Acceleration at the Alexandra CG Lab Jesper Bjerg Mosegaard, Head of Research and Innovation, Computer Graphics Lab, Alexandra Institute The Computer Graphics Lab at the Alexandra Institute does research and development within the topic of fast and accurate simulation and visualisation in high quality. This talk describes the role of the Alexandra Institute in transferring research to application in Danish Industry as well as specific opportunities for companies to benefit from the latest knowledge and technology. Dozens of Uses for Billions of Rays \u2013 a survey of ray tracing applications David McAllister, Optix Manager, NVIDIA Since introducing OptiX in 2009, NVIDIA has been approached by engineers from industries as diverse as geothermal exploration, cell phone antenna design, and automotive headlamp design that have one thing in common \u2013 the need to intersect rays, usually billions of them, against a database of geometry. I will survey many applications of ray tracing, within and beyond computer graphics, and show how accelerating ray tracing using GPUs addresses many challenges in industry. Scalable GPU computing service architecture: LEGO 3DServices Michael Sch\u00f8ler, Hinnerup.net og Henrik H\u00f8j Madsen, Solution Architect, Lego As LEGO is moving into the virtual playspace, a platform technology has been developed in-house primarily based on NVIDIA technologies, featuring: \u2022 CUDA, OptiX, OpenGL and general shaders \u2022 17 Quadro Plex in multiple environments, multiple datacentres \u2022 Advanced shading techniques for approaching high-quality results in real-time \u2022 On-demand asset generation \u2022 CDN assets distribution \u2022 A generic service-oriented interface \u2022 A distributed rendering architecture \u2022 Architectural patterns for distributed computing \u2022 A plugin architecture supporting existing and future LEGO experiences \u2022 A mentality shift from traditional ways of doing things on CPU vs GPU. \u2022 General experiences from developing on NVIDIA tech in a large-scale Enterprise setup The LEGO 3DServices system is designed to support diverse computational needs such as on-demand rendering, mesh optimisation, a Massive Multiplayer Online Game (MMO), product visualisations, 3D modeling and other current and future demanding computational tasks. Our aim with this session is to share our learnings and present LEGO\u2019s vision of the future of distributed GPU accelerated computation as a business-driven platform technology.<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2],"tags":[25,82],"_links":{"self":[{"href":"https:\/\/viscomp.alexandra.dk\/index.php?rest_route=\/wp\/v2\/posts\/1131"}],"collection":[{"href":"https:\/\/viscomp.alexandra.dk\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/viscomp.alexandra.dk\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/viscomp.alexandra.dk\/index.php?rest_route=\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/viscomp.alexandra.dk\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1131"}],"version-history":[{"count":0,"href":"https:\/\/viscomp.alexandra.dk\/index.php?rest_route=\/wp\/v2\/posts\/1131\/revisions"}],"wp:attachment":[{"href":"https:\/\/viscomp.alexandra.dk\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1131"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/viscomp.alexandra.dk\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1131"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/viscomp.alexandra.dk\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1131"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}