High Performance 3D Convolution for Protein Docking on IBM Blue Gene

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• 作者：Akira Nukada ; Yuichiro Hourai ; Akira Nishida ; Yutaka Akiyama
• 刊名：Lecture Notes in Computer Science
• 出版年：2007
• 出版时间：2007
• 年：2007
• 卷：4742
• 期：1
• 页码：958-969
• 全文大小：177 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

We have developed a high performance 3D convolution library for Protein Docking on IBM Blue Gene. The algorithm is designed to exploit slight locality of memory access in 3D-FFT by making full use of a cache memory structure. The 1D-FFT used in the 3D convolution is optimized for PowerPC 440 FP2 processors. The number of SIMOMD instructions is minimized by simultaneous computation of two 1D-FFTs. The high performance 3D convolution library achieves up to 2.16 Gflops (38.6% of peak) per node. The total performance of a shape complementarity search is estimated at 7 Tflops with the 4-rack Blue Gene system (4096 nodes).