Design and exploitation of a high-performance SIMD floating-point unit for Blue Gene/L

被引:26
作者
Chatterjee, S
Bachega, LR
Bergner, P
Dockser, KA
Gunnels, JA
Gupta, M
Gustavson, FG
Lapkowski, CA
Liu, GK
Mendell, M
Nair, R
Wait, CD
Ward, TJC
Wu, P
机构
[1] IBM Corp, Div Res, Thomas J Watson Res Ctr, Yorktown Hts, NY 10598 USA
[2] Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA
[3] IBM Corp, Syst & Technol Grp, Rochester, MN 55901 USA
[4] Qualcomm CDMA Technol, Cary, NC 27513 USA
[5] IBM Corp, Software Grp, Toronto Lab, Markham, ON L6G 1C7, Canada
[6] IBM United Kingdom Ltd, Winchester SO21 2JN, Hants, England
关键词
D O I
10.1147/rd.492.0377
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We describe the design of a dual-issue single-instruction, multiple-data-like (SIMD-like) extension of the IBM PowerPC((R)) 440 floating-point unit (FPU) core and the compiler and algorithmic techniques to exploit it. This extended FPU is targeted at both the IBM massively parallel Blue Gene((R))/L machine and the more pervasive embedded platforms. We discuss the hardware and software codesign that was essential in order to fully realize the performance benefits of the FPU when constrained by the memory bandwidth limitations and high penalties for misaligned data access imposed by the memory hierarchy on a Blue Gene/L node. Using both hand-optimized and compiled code for key linear algebraic kernels, we validate the architectural design choices, evaluate the success of the compiler, and quantify the effectiveness of the novel algorithm design techniques. Our measurements show that the combination of algorithm, compiler, and hardware delivers a significant fraction of peak floating-point performance for compute-bound-kernels, such (is matrix multiplication, (aid delivers a significant fraction of peak memory bandwidth for memory-bound kernels, such as DAXPY, while remaining largely insensitive to data alignment.
引用
收藏
页码:377 / 391
页数:15
相关论文
共 22 条
[1]   EXPLOITING FUNCTIONAL PARALLELISM OF POWER2 TO DESIGN HIGH-PERFORMANCE NUMERICAL ALGORITHMS [J].
AGARWAL, RC ;
GUSTAVSON, FG ;
ZUBAIR, M .
IBM JOURNAL OF RESEARCH AND DEVELOPMENT, 1994, 38 (05) :563-576
[2]  
ALMASI G, 2002, P IEEE INT SOL STAT, P196
[3]   A high-performance SIMD floating point unit for BlueGene/L: Architecture, compilation, and algorithm design [J].
Bachega, L ;
Chatterjee, S ;
Dockser, KA ;
Gunnels, JA ;
Gupta, M ;
Gustavson, FG ;
Lapkowski, CA ;
Liu, GK ;
Mendell, MP ;
Wait, CD ;
Ward, TJC .
13TH INTERNATIONAL CONFERENCE ON PARALLEL ARCHITECTURE AND COMPILATION TECHNIQUES, PROCEEDINGS, 2004, :85-96
[4]  
Briggs P., 1992, THESIS RICE U HOUSTO
[5]  
Clint Whaley R., 1998, P SC 98 P 1998 ACMIE, P38, DOI [10.5555/509058.509096, DOI 10.1109/SC.1998.10004]
[6]   AltiVec extension to PowerPC accelerates media processing [J].
Diefendorff, K ;
Dubey, PK ;
Hochsprung, R ;
Scales, H .
IEEE MICRO, 2000, 20 (02) :85-95
[7]  
DOCKSER K, 2001, IBM MICRONEWS, V7, P29
[8]  
DONGARRA JJ, 1990, ACM T MATH SOFTWARE, V16, P1, DOI 10.1145/77626.79170
[9]   Vectorization for SIMD Architectures with alignment constraints [J].
Eichenberger, AE ;
Wu, P ;
O'Brien, K .
ACM SIGPLAN NOTICES, 2004, 39 (06) :82-93
[10]  
GOTO K, 2002, TR200255 U TEX AUST