Parallel Scalability of a Fine-Grain Prestack Reverse Time Migration Algorithm

Nunes-do-Rosario, Desnes A.; Xavier‐de‐Souza, Samuel; Maciel, Rosangela Corrêa; Costa, Jessé C.

doi:10.1109/lgrs.2015.2482481

Cited by 12 publications

(5 citation statements)

References 18 publications

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“…The article focused on a discussion without showing any measured results. Nunes‐do‐Rosario et al 32 implemented a parallel version of a RTM algorithm for AMD processors. They achieved a speedup of 17× on a 24‐core processor.…”

Section: Related Work and Motivationmentioning

confidence: 99%

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Energy efficiency and portability of oil and gas simulations on multicore and graphics processing unit architectures

Serpa

Pavan

Cruz

et al. 2021

Concurrency and Computation

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Summary Reverse time migration (RTM) simulation is the basis of the seismic imaging tools used by the oil and gas industry. Developers have been porting their simulations to the new high‐performance computing architectures, providing faster and more accurate results at each new generation. However, several challenges arrive when trying to achieve high performance on these new architectures. The first one is to choose the architecture that best fits the kind of simulation. After that, researchers should choose the API used to implement the simulation code. These two decisions are strongly related to the effort, performance, and energy efficiency of the simulations. In this article, we propose three optimizations for an oil and gas application, which reduce the floating‐point operations by changing the equation derivatives. We evaluate these optimizations in different multicore and GPU architectures, investigating the impact of different APIs on the performance, energy efficiency, and portability of the code. Our experimental results show that the dedicated CUDA implementation running on the NVIDIA Volta architecture has the best performance and energy efficiency for RTM on GPUs, while the OpenMP version is the best for Intel Broadwell in the multicore. Also, the OpenACC version, which has a lower programming effort and executes on both architectures, has an up to 20% better performance and energy efficiency than the nonportable ones.

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Section: Related Work and Motivationmentioning

confidence: 99%

“…Nunes‐do‐Rosario et al 32 and Nesi et al 35 designed parallel versions of CFD simulations using different parallel programming paradigms. However, they do not take into account portability and energy efficiency.…”

Section: Related Work and Motivationmentioning

confidence: 99%

Energy efficiency and portability of oil and gas simulations on multicore and graphics processing unit architectures

Serpa

Pavan

Cruz

et al. 2021

Concurrency and Computation

View full text Add to dashboard Cite

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“…The RTM method used in the experiments described in this paper is an extension of the RTM introduced by Nunes-do-Rosario et al [19]. It is implemented in C with a hybrid parallel approach.…”

Section: Rtm and Static Load Balancingmentioning

confidence: 99%

Distributed-Memory Load Balancing With Cyclic Token-Based Work-Stealing Applied to Reverse Time Migration

et al. 2019

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Reverse time migration (RTM) is a prominent technique in seismic imaging. Its resulting subsurface images are used in the industry to investigate with higher confidence the existence and the conditions of oil and gas reservoirs. Because of its high computational cost, RTM must make use of parallel computers. Balancing the workload distribution of an RTM is a growing challenge in distributed computing systems. The competition for shared resources and the differently-sized tasks of the RTM are some of the possible sources of load imbalance. Although many load balancing techniques exist, scaling up for large problems and large systems remains a challenge because synchronization overhead also scales. This paper proposes a cyclic token-based work-stealing (CTWS) algorithm for distributed memory systems applied to RTM. The novel cyclic token approach reduces the number of failed steals, avoids communication overhead, and simplifies the victim selection and the termination strategy. The proposed method is implemented as a C library using the one-sided communication feature of the message passing interface (MPI) standard. Results obtained by applying the proposed technique to balance the workload of a 3D RTM system present a factor of 14.1 % speedup and reductions of the load imbalance of 78.4 % when compared to the conventional static distribution. 1The migration of seismic data is the process that attempts to build an image of the Earth's interior from recorded field data. Migration places these data into their actual geological position in the subsurface using numerical approximations of either wave-theoretical or ray-theoretical approaches to simulate the propagation of seismic waves [1].The wave-theoretical approach to the propagation of seismic waves employs the finite difference method (FDM) [2,3] to numerically solve the equation describing the movement of the waves [1,4]. This approach is prevalent among the geophysical community, due to its capacity of dealing with substantial velocity variations in complex geology (e.g., pre-salt).Reverse time migration (RTM) [5-9] implements this approach. It is one of the most known FDM-based migration methods. RTM is computationally intensive in terms of data storage and handling, and its use of high-complexity algorithms. Therefore, exploiting parallelism is mandatory for RTM implementations in 3D Earth models (3D RTM) [10].Parallel architectures can be classified as shared memory, when there is a single memory address space available to all processing units (e.g., nodes or cores), or distributed memory otherwise [11]. Many scientific and industrial computational resources are distributed memory systems composed of multiprocessor nodes with shared memory systems. A hybrid parallel application works at these two levels of parallelism. It can distribute the total workload among the nodes of a distributed memory system. Each node, then, distributes its subset of the workload among the processing units of its shared memory system. Parallel machines can also be described as het...

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“…Therefore, the computational cost is the main factor limiting the application of RTM, as well as for several other geophysical algorithms [4], [5]. For this reason, parallel computing techniques have been widely applied to these methods (e.g., [6]).…”

Section: Introductionmentioning

confidence: 99%

Auto-Tuning of Dynamic Scheduling Applied to 3D Reverse Time Migration on Multicore Systems

et al. 2020

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Reverse time migration (RTM) is an algorithm widely used in the oil and gas industry to process seismic data. It is a computationally intensive task that suits well in parallel computers. Methods such as RTM can be parallelized in shared memory systems through scheduling iterations of parallel loops to threads. However, several aspects, such as memory size and hierarchy, number of cores, and input size, make optimal scheduling very challenging. In this paper, we introduce a run-time strategy to automatically tune the dynamic scheduling of parallel loops iterations in iterative applications, such as the RTM, in multicore systems. The proposed method aims to reduce the execution time of such applications. To find the optimal granularity, we propose a coupled simulated annealing (CSA) based auto-tuning strategy that adjusts the chunk size of work that OpenMP parallel loops assign dynamically to worker threads during the initialization of a 3D RTM application. Experiments performed with different computational systems and input sizes show that the proposed method is consistently better than the default OpenMP schedulers, static, auto, and guided, causing the application to be up to 33% faster. We show that the possible reason for this performance is the reduction of cache misses, mainly level L3, and low overhead, inferior to 2%. Having shown to be robust and scalable for the 3D RTM, the proposed method could also improve the performance of similar wave-based algorithms, such as full-waveform inversion (FWI) and other iterative applications.

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Parallel Scalability of a Fine-Grain Prestack Reverse Time Migration Algorithm

Cited by 12 publications

References 18 publications

Energy efficiency and portability of oil and gas simulations on multicore and graphics processing unit architectures

Energy efficiency and portability of oil and gas simulations on multicore and graphics processing unit architectures

Distributed-Memory Load Balancing With Cyclic Token-Based Work-Stealing Applied to Reverse Time Migration

Auto-Tuning of Dynamic Scheduling Applied to 3D Reverse Time Migration on Multicore Systems

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