Generating SIMD vectorized permutations

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

Volumn 4959 LNCS, Issue , 2008, Pages 116-131

  Franchetti, Franz ^a   Püschel, Markus ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BASIC IDEA; COMPILER CONSTRUCTION; CONFERENCES (CHEMICAL INDUSTRY); EUROPEAN; FOURIER; HEIDELBERG (CO); INTERNATIONAL CONFERENCES; KRONECKER PRODUCTS; PERMUTATION (PERM); REWRITING SYSTEMS; SEARCH MECHANISMS; VECTOR INSTRUCTIONS;

BASIC (PROGRAMMING LANGUAGE); FAST FOURIER TRANSFORMS; FOURIER TRANSFORMS; MACHINE DESIGN; MACHINE VIBRATIONS; MATRIX ALGEBRA; PROGRAM COMPILERS; SECURITY OF DATA;

VECTORS;

EID: 47249121824     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-78791-4_8     Document Type: Conference Paper

References (14)

1. van Loan, C.: Computational Framework of the Fast Fourier Transform. SIAM, Philadelphia (1992)
2. Püschel, M., Moura, J.M.F., Johnson, J., Padua, D., Veloso, M., Singer, B.W., Xiong, J., Franchetti, F., Gačić, A., Voronenko, Y., Chen, K., Johnson, R.W., Rizzolo, N.: SPIRAL: Code generation for DSP transforms. Proceedings of the IEEE 93(2), 232-275 (2005); Special issue on Program Generation, Optimization, and Adaptation
3. Franchetti, F., Voronenko, Y., Püschel, M.: A rewriting system for the vectorization of signal transforms. In: Proc. High Performance Computing for Computational Science (VECPAR) (2006)
4. Franchetti, F., Püschel, M.: Short vector code generation for the discrete Fourier transform. In: Proc. IEEE Int'l Parallel and Distributed Processing Symposium (IPDPS), pp. 58-67 (2003)
5. Nuzman, D., Rosen, I., Zaks, A.: Auto-vectorization of interleaved data for SIMD. In: Proc. Programming Language Design and Implementation (PLDI), pp. 132-143 (2006)
6. Johnson, J.R., Johnson, R.W., Rodriguez, D., Tolimieri, R.: A methodology for designing, modifying, and implementing FFT algorithms on various architectures. Circuits Systems Signal Processing 9, 449-500 (1990)
7. Floyd, R.W.: Permuting information in idealized two-level storage. Complexity of Computer Calculations, 105-109 (1972)
8. Vitter, J.S., Shriver, E.A.M.: Algorithms for parallel memory I: Two-level memories. Algorithmica 12(2/3), 110-147 (1994)
9. Suh, J., Prasanna, V.: An efficient algorithm for out-of-core matrix transposition. IEEE Transactions on Computers 51(6), 420-438 (2002)
10. Lu, Q., Krishnamoorthy, S., Sadayappan, P.: Combining analytical and empirical approaches in tuning matrix transposition. In: Proc. Parallel Architectures and Compilation Techniques (PACT), pp. 233-242 (2006)
11. Zima, H., Chapman, B.: Supercompilers for parallel and vector computers. ACM Press, New York (1990)
12. Ren, G., Wu, P., Padua, D.: Optimizing data permutations for SIMD devices. In: Proc. Programming Language Design and Implementation (PLDI), pp. 118-131 (2006)
13. Xiong, J., Johnson, J., Johnson, R., Padua, D.: SPL: A language and compiler for DSP algorithms. In: Proc. Programming Language Design and Implementation (PLDI), pp. 298-308 (2001)
14. Dershowitz, N., Plaisted, D.A.: Rewriting. In: Robinson, A., Voronkov, A. (eds.) Handbook of Automated Reasoning, vol. 1, pp. 535-610. Elsevier, Amsterdam (2001)