Generating Optimized Sparse Matrix Vector Product over Finite Fields

نویسندگان

  • Pascal Giorgi
  • Bastien Vialla
چکیده

Sparse Matrix Vector multiplication (SpMV) is one of the most important operation for exact sparse linear algebra. A lot of research has been done by the numerical community to provide efficient sparse matrix formats. However, when computing over finite fields, one need to deal with multi-precision values and more complex operations. In order to provide highly efficient SpMV kernel over finite field, we propose a code generation tool that uses heuristics to automatically choose the underlying matrix representation and the corresponding arithmetic.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Efficient massively parallel implementation of the ReLPM exponential integrator for advection-diffusion models∗†

This work considers the Real Leja Points Method (ReLPM), [J. Comput. Appl. Math., 172 (2004), pp. 79–99], for the exponential integration of large-scale sparse systems of ODEs, generated by Finite Element or Finite Difference discretizations of 3-D advectiondiffusion models. We present an efficient parallel implementation of ReLPM for polynomial interpolation of the matrix exponential propagato...

متن کامل

Solving sparse linear equations over finite fields

Ahstruct-A “coordinate recurrence” method for solving sparse systems of linear equations over finite fields is described. The algorithms discussed all require O( n,( w + nl) logkn,) field operations, where nI is the maximum dimension of the coefficient matrix, w is approximately the number of field operations required to apply the matrix to a test vector, and the value of k depends on the algor...

متن کامل

A massively parallel exponential integrator for advection-diffusion models

This work considers the Real Leja Points Method (ReLPM), [M. Caliari, M. Vianello, L. Bergamaschi, Interpolating discrete advection-diffusion propagators at spectral Leja sequences, J. Comput. Appl. Math. 172 (2004) 79–99], for the exponential integration of large-scale sparse systems of ODEs, generated by Finite Element or Finite Difference discretizations of 3-D advection-diffusion models. We...

متن کامل

Performance Improvement of Sparse Matrix Vector Product on Vector Machines

Many applications based on finite element and finite difference methods include the solution of large sparse linear systems using preconditioned iterative methods. Matrix vector multiplication is one of the key operations that has a significant impact on the performance of any iterative solver. In this paper, recent developments in sparse storage formats on vector machines are reviewed. Then, s...

متن کامل

Run-Time Optimization of Sparse Matrix-Vector Multiplication on SIMD Machines

Sparse matrix-vector multiplication forms the heart of iterative linear solvers used widely in scientific computations (e.g., finite element methods). In such solvers, the matrix-vector product is computed repeatedly, often thousands of times, with updated values of the vector until convergence is achieved. In an SIMD architecture, each processor has to fetch the updated off-processor vector el...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014