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Eliminating the Memory Bottleneck: An FPGA-based Solution for 3D Reverse Time Migration

机译:消除内存瓶颈:基于FPGA的3D相反时间迁移解决方案

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Memory-related constraints (memory bandwidth, cache size) are nowadays the performance bottleneck of most computational applications. Especially in the scenario of multiple cores, the performance does not scale with the number of cores in many cases. In our work, we present our FPGA-based solution for the 3D Reverse Time Migration (RTM) algorithm. As the most computationally demanding imaging algorithm in current oil and gas exploration, RTM involves various computational challenges, such as a high demand for storage size and bandwidth, and a poor cache behavior. Combining optimizations from both the algorithmic and architectural perspectives, our FPGA-based solution manages to remove the memory constraints and provide a high performance that can scale well with the amount of computational resources available. Compared with an optimized CPU implementation using two quad-core Intel Nehalem CPUs, our solution achieves 4× speedup on two Virtex-5 FPGAs, and 8× speedup on two Virtex-6 FPGAs. Our projection demonstrates that the performance will continue to scale with the future increase of FPGA capacities.
机译:现在,内存相关的约束(内存带宽,缓存大小)是大多数计算应用程序的性能瓶颈。特别是在多个核心的场景中,在许多情况下,性能不会随着核心的数量扩展。在我们的工作中,我们展示了基于FPGA的解决方案,用于3D相反时间迁移(RTM)算法。作为当前石油和天然气勘探中最具计算的苛刻的成像算法,RTM涉及各种计算挑战,例如对存储大小和带宽的高需求,以及较差的缓存行为。基于FPGA的解决方案组合了从算法和架构角度的优化,管理到删除内存约束,并提供可以使用可用计算资源的量扩展的高性能。与使用两个四核Intel Nehalem CPU的优化CPU实现相比,我们的解决方案在两个Virtex-5 FPGA上实现了4倍的加速,以及两个Virtex-6 FPGA上的8×加速。我们的预测表明,随着FPGA容量的未来增加,性能将继续规模。

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