A code generation approach for auto-vectorization in the SPADE compiler

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5898 LNCS, Issue , 2010, Pages 383-390

  Wang, Huayong ^a   Andrade, Henrique ^b   Gedik, Buǧra ^b   Wu, Kun Lung ^b  

^a IBM CHINA RESEARCH LAB   (China)

^b IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

C++ LIBRARIES; CODE GENERATION; DATA TYPE; LANGUAGE EXTENSIONS; PROGRAMMING LANGUAGE; STREAM PROCESSING; VECTORIZATION;

COMPUTER HARDWARE DESCRIPTION LANGUAGES; HYDRAULICS; LINGUISTICS; PARALLEL ARCHITECTURES; QUERY LANGUAGES;

PROGRAM COMPILERS;

EID: 77954400615     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-13374-9_26     Document Type: Conference Paper

References (20)

1. Jain, N., Amini, L., Andrade, H., King, R., Park, Y., Selo, P., Venkatramani, C.: Design, implementation, and evaluation of the linear road benchmark on the stream processing core. In: Proceedings of the International Conference on Management of Data (SIGMOD 2006), Chicago, IL (2006)
2. Wu, K.L., Yu, P.S., Gedik, B., Hildrum, K.W., Aggarwal, C.C., Bouillet, E., Fan, W., George, D.A., Gu, X., Luo, G., Wang, H.: Challenges and experience in prototyping a multi-modal stream analytic and monitoring application on System S. In: Proceedings of the International Conference on Very Large Data Bases Conference (VLDB 2007), Vienna, Austria (2007)
3. Arasu, A., Babcock, B., Babu, S., Datar, M., Ito, K., Motwani, R., Nishizawa, I., Srivastava, U., Thomas, D., Varma, R., Widom, J.: STREAM: The Stanford stream data manager. IEEE Data Engineering Bulletin 26 (2003)
4. Abadi, D.J., Ahmad, Y., Balazinska, M., Cetintemel, U., Cherniack, M., Hwang, J.H., Lindner, W., Maskey, A.S., Rasin, A., Ryvkina, E., Tatbul, N., Xing, Y., Zdonik, S.: The design of the Borealis stream processing engine. In: Proceedings of Conference on Innovative Data Systems Research (CIDR 2005), Asilomar, CA (2005)
5. StreamBase: StreamBase Systems, http://www.streambase.com
6. Chandrasekaran, S., Cooper, O., Deshpande, A., Franklin, M.J., Hellerstein, J.M., Hong, W., Krishnamurthy, S., Madden, S.R., Raman, V., Reiss, F., Shah, M.A.: TelegraphCQ: Continuous dataflow processing for an uncertain world. In: Proceedings of Conference on Innovative Data Systems Research (CIDR 2003), Asilomar, CA (2003)
7. Thies, W., Karczmarek, M., Amarasinghe, S.: StreamIt: A language for streaming applications. In: Proceedings of the 2002 International Conference on Compiler Construction (ICCC 2002), Grenoble, France (2002)
8. Upadhyaya, G., Pai, V.S., Midkiff, S.P.: Expressing and exploiting concurrency in networked applications with Aspen. In: Proceedings of the 2007 Symposium on Principles and Practice of Parallel Programming, PPOPP 2007 (2007)
9. Aberdeen, D., Baxter, J.: Emmerald: a fast matrix-matrix multiply using Intel's SSE instructions. Concurrency and Computation: Practice and Experience 13, 103-119 (2001) (Pubitemid 32432113)
10. Conte, G., Tommesani, S., Zanichelli, F.: The long and winding road to high-performance image processing with MMX/SSE. In: 5th International Workshop on Computer Architectures for Machine Perception (CAMP 2000), Washington, DC, USA, p. 302 (2000)
11. Diefendorff, K., Dubey, P.K., Hochsprung, R., Scales, H.: AltiVec extension to PowerPC accelerates media processing. IEEE Micro 20(2), 85-95 (2000) (Pubitemid 30585387)
12. Puschel, F.F.M.: Short vector code generation for the discrete fourier transform. In: Proceedings of the International Conference on Parallel and Distributed Systems (IPDPS 2003), Nice, France (2003)
13. Gedik, B., Andrade, H., Wu, K.L., Yu, P.S., Doo, M.: SPADE: The System S declarative stream processing engine. In: Proceedings of the International Conference on Management of Data (SIGMOD 2008), Vancouver, Canada (2008)
14. Hirzel, M., Andrade, H., Gedik, B., Kumar, V., Rosa, G., Soule, R., Wu, K.L.: Spade - language specification. Technical Report RC24830, IBM Research (2009)
15. Intel: Intel 64 and IA-32 architectures optimization reference manual (November 2007), http://www.intel.com/design/processor/manuals/248966.pdf
16. Naishlos, D.: Autovectorization in GCC. In: Proceedings of the GCC Summit (2004)
17. Wu, X., Kumar, V., Quinlan, J.R., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G.J., Ng, A., Liu, B., Yu, P.S., Zhou, Z.H., Steinbach, M., Hand, D.J., Steinberg, D.: Top 10 algorithms in data mining. Knowledge and Information Systems 14(1), 1-37 (2008)
18. Meerwald, P.: Digital watermarking project, http://www.cosy.sbg.ac.at/ ~pmeerw/Watermarking
19. Laidi, K., Bailiche, M.A., Mehenni, M.: Comparative study of block matching techniques used in video images motions estimation. In: Stojmenovic, I., Thulasiram, R.K., Yang, L.T., Jia, W., Guo, M., de Mello, R.F. (eds.) ISPA 2007. LNCS, vol. 4742. Springer, Heidelberg (2007)
20. Intel: Intel C++ compiler user and reference guides. Intel Document number: 304968-022US (2008)