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

机译:消除存储瓶颈:基于FPGA的3D逆向时间迁移解决方案

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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:如今,与内存相关的约束(内存带宽,缓存大小)已成为大多数计算应用程序的性能瓶颈。尤其是在多核的情况下,在许多情况下,性能不会随核的数量而扩展。在我们的工作中,我们介绍了基于FPGA的3D反向时间迁移(RTM)算法的解决方案。作为当前石油和天然气勘探中计算量最大的成像算法,RTM涉及各种计算挑战,例如对存储大小和带宽的高要求以及较差的缓存行为。结合算法和架构方面的优化,我们基于FPGA的解决方案设法消除了内存限制,并提供了一种高性能,可以在可用的计算资源量下很好地扩展。与使用两个四核Intel Nehalem CPU的优化CPU实施相比,我们的解决方案在两个Virtex-5 FPGA上实现了4倍的加速,在两个Virtex-6 FPGA上实现了8倍的加速。我们的预测表明,性能将随着FPGA容量的未来增长而继续扩展。

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