Sepia: scalable 3D compositing using PCI Pamette

Moll, Laurent; Heirich, Alan; Shand, M.

doi:10.1109/fpga.1999.803676

Cited by 39 publications

(22 citation statements)

References 8 publications

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“…Using ASC, we map all the arithmetic units onto the Sepia card [16] and Xilinx Virtex-II XC2V6000 FPGA to test their performance and hardware cost. Table 3 shows the area and latency of the LNS arithmetic units automatically produced by our generator, compared with the designs in [2].…”

Section: Experiments Results For Lns Arithmetic Unitsmentioning

confidence: 99%

Optimizing Logarithmic Arithmetic on FPGAs

Sotiriades

Dollas

2007

15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM 2007)

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Section: Experiments Results For Lns Arithmetic Unitsmentioning

confidence: 99%

Optimizing Logarithmic Arithmetic on FPGAs

Sotiriades

Dollas

2007

15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM 2007)

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“…The Sepia architecture is an FPGA and network-based subsystem for interactive parallel visualization using remote displays and commodity graphics accelerators [13,14]. The architecture allows general "sort-last" style parallel programming [16] and supports other programming models by providing concurrent high speed compositing of large numbers of image streams.…”

Section: Sepia Architecturementioning

confidence: 99%

“…In previous work [13,14] a commodity-based architecture (Sepia) was presented for constructing scalable display subsystems for distributed clusters. The architecture allows large numbers of computers to post images onto rectilinear tiles of a large display, and to apply compositing, blending, and other per-pixel operators to those images.…”

Section: Introductionmentioning

confidence: 99%

Scalable interactive volume rendering using off-the-shelf components

Lombeyda

Moll²,

Shand³

et al.

Proceedings IEEE 2001 Symposium on Parallel and Large-Data Visualization and Graphics (Cat. No.01EX520)

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This paper describes an application of a second generation implementation of the Sepia architecture (Sepia-2) to interactive volumetric visualization of large rectilinear scalar fields. By employing pipelined associative blending operators in a sort-last configuration a demonstration system with 8 rendering computers sustains 24 to 28 frames per second while interactively rendering large data volumes (1024x256x256 voxels, and 512x512x512 voxels). We believe interactive performance at these frame rates and data sizes is unprecedented. We also believe these results can be extended to other types of structured and unstructured grids and a variety of GL rendering techniques including surface rendering and shadow mapping. We show how to extend our single-stage crossbar demonstration system to multi-stage networks in order to support much larger data sizes and higher image resolutions. This requires solving a dynamic mapping problem for a class of blending operators that includes Porter-Duff compositing operators.

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“…Due to its conceptual simplicity, a number of special-purpose image compositing hardware solutions for sort-last parallel rendering have been developed. The proposed hardware architectures include Sepia [38,32], Sepia 2 [35,36], Lightning 2 [52], Metabuffer [9,59], MPC Compositor [43] and PixelFlow [40,17], of which only a few have reached the commercial product stage (i.e. Sepia 2 and MPC Compositor).…”

Section: Special-purpose Architecturesmentioning

confidence: 99%

Equalizer: A Scalable Parallel Rendering Framework

Eilemann

Makhinya

Pajarola

2009

IEEE Trans. Visual. Comput. Graphics

143

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Abstract-Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering solutions that can exploit multipipe hardware accelerated graphics. In fact, to achieve interactive visualization, scalable rendering systems are essential to cope with the rapid growth of data sets. However, parallel rendering systems are non-trivial to develop and often only application specific implementations have been proposed. The task of developing a scalable parallel rendering framework is even more difficult if it should be generic to support various types of data and visualization applications, and at the same time work efficiently on a cluster with distributed graphics cards. In this paper we introduce a novel system called Equalizer, a toolkit for scalable parallel rendering based on OpenGL which provides an application programming interface (API) to develop scalable graphics applications for a wide range of systems ranging from large distributed visualization clusters and multi-processor multipipe graphics systems to single-processor single-pipe desktop machines. We describe the system architecture, the basic API, discuss its advantadges over previous approaches, present example configurations and usage scenarios as well as scalability results.

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Sepia: scalable 3D compositing using PCI Pamette

Cited by 39 publications

References 8 publications

Optimizing Logarithmic Arithmetic on FPGAs

Optimizing Logarithmic Arithmetic on FPGAs

Scalable interactive volume rendering using off-the-shelf components

Equalizer: A Scalable Parallel Rendering Framework

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