Applied Parallel Computing. New Paradigms for HPC in by Jari Järvinen, Juha Haataja, Jari Hämäläinen (auth.), Tor

By Jari Järvinen, Juha Haataja, Jari Hämäläinen (auth.), Tor Sørevik, Fredrik Manne, Assefaw Hadish Gebremedhin, Randi Moe (eds.)

The papers during this quantity have been offered at PARA 2000, the 5th overseas Workshop on utilized Parallel Computing. PARA 2000 used to be held in Bergen, Norway, June 18-21, 2000. The workshop was once prepared by way of Parallab and the dept of Informatics on the college of Bergen. the overall topic for PARA 2000 was once New paradigms for HPC in and academia concentrating on: { High-performance computing purposes in academia and undefined, { using Java in high-performance computing, { Grid and Meta computing, { instructions in high-performance computing and networking, { schooling in Computational technology. The workshop incorporated nine invited shows and 39 contributed pres- tations. The PARA 2000 assembly all started with a one-day educational on OpenMP programming led via Timothy Mattson. This used to be by means of a three-day wor- hop. The rst 3 PARA workshops have been held on the Technical college of Denmark (DTU), Lyngby (1994, 1995, and 1996). Following PARA’96, an - ternational steerage committee for the PARA conferences used to be appointed and the committee determined workshop should still occur each moment 12 months in a single of the Nordic international locations. The 1998 workshop used to be held at Ume a college, Sweden. One very important objective of those workshops is to bolster the binds among HPC facilities, academia, and within the Nordic nations in addition to around the globe. The college of Bergen equipped the 2000 workshop and the subsequent workshop within the yr 2002 will occur on the Helsinki collage of know-how, Espoo, Finland.

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Applied Parallel Computing. New Paradigms for HPC in Industry and Academia: 5th International Workshop, PARA 2000 Bergen, Norway, June 18–20, 2000 Proceedings

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Extra info for Applied Parallel Computing. New Paradigms for HPC in Industry and Academia: 5th International Workshop, PARA 2000 Bergen, Norway, June 18–20, 2000 Proceedings

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They are listed in figs. 31 and 32. Recursive Algorithm 31 Recursive LU factorization without pivoting (rgausslu): Do recursion • if min(m, n) > 1 then • (L1 , U1 ) = rgausslu of A1 • L11 U12 = A12 → RTRSM • Aˆ22 = A22 − L21 U12 → GEMM • (L22 , U22 ) = rgausslu of Aˆ22 • otherwise • L1 := A1 /a11 and U1 = a11 End recursion • if n > m then • L U3 = A3 → RTRSM Linear Algebra with Recursive Algorithms 43 D_RP_PPTRF performance on IBM 1 proc. PowerPC 604e 332 MHz 500 LAPACK full(L) LAPACK full(U) Recursive packed(L) Recursive packed(U) LAPACK packed(L) LAPACK packed(U) 450 400 350 Mflop/s 300 250 200 150 100 50 0 0 500 1000 1500 2000 matrix size 2500 3000 3500 4000 D_RP_PPTRS performance on IBM 1 proc.

36. Peng Wu, Sam Midkiff, Jos´e Moreira, and Manish Gupta. Efficient support for complex numbers in Java. In ACM 1999 Java Grande Conference, pages 109–118, San Francisco, June 12–14, 1999. 37. Abraham Ziv. Fast evaluation of elementary mathematical functions with correctly rounded last bit. ACM Transactions on Mathematical Software, (17):410–423, 1991. no Abstract. The availability of new powerful super computers has lead to new activities in high resolution ocean prediction and data assimilation.

SYRK performs one of the symmetric rank k operations: C := αAAT + βC or C := αAT A + βC where α and β are scalars. A is a rectangular matrix (m × n). C is a square symmetric matrix. We will introduce the recursive formulation only for one of the four cases of SYRK: C := αAAT + βC. S. Andersen et al. The matrices A and C can be partitioned into smaller submatrices: C11 C21 C22 =β C11 C21 C22 +α A11 A12 A21 A22 A11 A12 A21 A22 T . The matrices A11 = A(1 : h, 1 : p), A12 = A(1 : h, p+1 : n), A21 = A(h+1 : m, 1 : p), A22 = A(h + 1 : m, p + 1 : n), C11 = C(1 : h, 1 : h), C21 = C(h + 1 : m, 1 : h), C22 = C(h + 1 : m, h + 1 : m) are submatrices of A and C respectively, and h = m/2 and p = n/2.

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