Computational Characteristics of Production Seismic Migration and its Performance on Novel Processor Architectures

Panetta, Jairo; Filho, P.R.P. de Souza; Filho, Carlos Alves da Cunha; Motta, Fernando M. Roxo da; Pinheiro, Silvio Sinedino; Pedrosa, Iván; Rosa, Andre Luiz Romanelli; Monnerat, Luiz; Carneiro, L.; Albrecht, Carlos

doi:10.1109/sbac-pad.2007.13

Cited by 20 publications

(14 citation statements)

References 5 publications

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“…However, because the size of input survey data grows continuously over time, a single modern Kirchhoff migration requires weeks of processing on large x86-based clusters [1], encouraging the use of larger machines and hardware accelerators.…”

Section: Related Workmentioning

confidence: 99%

“…In a previous article, we reported the performance of Petrobras's Kirchhoff time migration production code on x86 clusters, on an IBM Blue Gene machine and on a small cluster of STI Cell [1]. In a related article [2], we explored code structure characteristics that allow multi-algorithm support, and we summarized performance data (speed/core and speed/watt) for a large set of computer architectures, including GPUs.…”

Section: Related Workmentioning

confidence: 99%

“…During the last four years, we conducted a research project at Petrobras to test the adequacy of innovative computing architectures for seismic processing. As early project experiments indicated, recently released GPUs deliver considerable gains compared to x86-based hardware in terms of speed per power, speed per area and speed per price [1,2]. Based on these conclusions, Petrobras acquired a cluster of 32 dual processor 2.33 GHz Xeon 5410 quad-core nodes, accelerated by two NVIDIA Tesla C1060 GPUs per node, to test the adequacy of this architecture for a Kirchhoff prestack time and depth seismic migration code, which was developed in-house and is used daily in production runs.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Accelerating Time and Depth Seismic Migration by CPU and GPU Cooperation

Panetta

Teixeira

Filho

et al. 2011

Int J Parallel Prog

Self Cite

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In this paper, we discuss the porting strategy and the achieved performance of Petrobras production code that implements Kirchhoff prestack time and depth seismic migration algorithms on a cluster of 64 GPUs and 256 CPU cores. The time migration of a real-world survey was 20 times faster in the full cluster with GPUs than in the full cluster without GPUs. The introduction of GPUs accelerated the depth migration of another real-world survey by a factor of 5. In both cases, a large fraction of the achieved gains were due to the porting strategy that privileges CPU-GPU A preliminary version of this work was published at the 21st International Symposium on Computer Architecture and High Performance Computing, SBAC-PAD 2009. 123 Int J Parallel Prog (2012) 40:290-312 291cooperation instead of pure GPU speed. Another strategy that contributed to the high gains was GPU overloading by multiple MPI processes. To cope with the heterogeneous load of real-world data, we developed a dynamic load balancing scheme that significantly speeds up computation.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Accelerating Time and Depth Seismic Migration by CPU and GPU Cooperation

Panetta

Teixeira

Filho

et al. 2011

Int J Parallel Prog

Self Cite

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“…In addition, for faster processing hardware, the FPGA allows a reduction of energy costs as indicated for this type of operator when compared with CPU or GPU approaches. This power speedup when associated with companies like Petrobras, that has clusters in order of #5000 CPUs [8], which continuously studies aimed at obtaining the subsurface oil, has a very high impact allowing considerable reductions in energy consumption in the company. …”

Section: A Performance and Power Estimatesmentioning

confidence: 99%

An FPGA-Based Accelerator to Speed-Up Matrix Multiplication of Floating Point Operations

Holanda

Pimentel

Barbosa

et al. 2011

2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PHD Forum

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Field Programmable Gate Arrays (FPGAs) are able to provide a high computational parallelism that can be exploited to achieve high performance improvements in intensive data processing problems. In this paper our efforts were directed towards developing a PC cluster based on nodes that use FPGAs as co-processors. The target application is a floating-point large dense matrix multiplication. Experimental results for just one node of the cluster, consisting of a Xilinx Virtex 5 VLX50T with a PCI interface, showed performance improvements compared with the Intel Core2 Quad at 2.66 GHz, achieving a speed-up of 1.19 times. Other analyses in terms of frequency variation and power dissipation have been made by considering different matrix sizes running in one node of the cluster. Recently, the platform has been updated for a powerful Gidel plaftorm, the PROCe III 260E. This new platform consists of 1 FPGA Stratix III per board. In this board, it is possible to allocate up to 40 MACs per FPGA, reaching an overall speed-up of approximately 11.2 per node of the cluster when compared with the same general-purpose processor. A full example is presented in this paper.

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“…Unlike other clusters designed to focus on specific application demands [17,21], Netuno must support a wide range of different types of computations. So, the architectural decisions were not target to particular needs, they have to be general enough to encompass different computational demands.…”

Section: Introductionmentioning

confidence: 99%

The Experience in Designing and Building the High Performance Cluster Netuno

Silva¹,

Correa²,

Bentes

et al. 2011

2011 23rd International Symposium on Computer Architecture and High Performance Computing

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This paper presents a description and the evaluation of the Netuno supercomputer, a high-performance cluster installed at Federal University of Rio de Janeiro in Brazil.The results for the High Performance Linpack (HPL) benchmark and two real applications are reported. Since building a high-performance cluster for running a wide range of applications is a non-trivial task, some lessons learned from assembling and operating this cluster, such as the excelent performance of the OpenMPI library, and the importance of the use an efficient parallel file system over the traditional NFS system, can be useful knowledge to support the design of new systems. Currently, Netuno is being heavily used to run large scale simulations in the areas of ocean modeling, meteorology, engineering, physics, and geophysics.

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Computational Characteristics of Production Seismic Migration and its Performance on Novel Processor Architectures

Cited by 20 publications

References 5 publications

Accelerating Time and Depth Seismic Migration by CPU and GPU Cooperation

Accelerating Time and Depth Seismic Migration by CPU and GPU Cooperation

An FPGA-Based Accelerator to Speed-Up Matrix Multiplication of Floating Point Operations

The Experience in Designing and Building the High Performance Cluster Netuno

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