A Hilbert-order multiplication scheme for unstructured sparse matrices
نویسندگان
چکیده
We investigate a new storage format for unstructured sparse matrices, based on the space filling Hilbert curve. Numerical tests with matrix-vector multiplication show the potential of the fractal storage format (FS) in comparison to the traditional compressed row storage format (CRS). The FS format outperforms the CRS format by up to 50% for matrix-vector multiplications with multiple right hand sides.
منابع مشابه
A cache-oblivious sparse matrix–vector multiplication scheme based on the Hilbert curve
The sparse matrix–vector (SpMV) multiplication is an important kernel in many applications. When the sparse matrix used is unstructured, however, standard SpMV multiplication implementations typically are inefficient in terms of cache usage, sometimes working at only a fraction of peak performance. Cache-aware algorithms take information on specifics of the cache architecture as a parameter to ...
متن کاملA New Method for Speech Enhancement Based on Incoherent Model Learning in Wavelet Transform Domain
Quality of speech signal significantly reduces in the presence of environmental noise signals and leads to the imperfect performance of hearing aid devices, automatic speech recognition systems, and mobile phones. In this paper, the single channel speech enhancement of the corrupted signals by the additive noise signals is considered. A dictionary-based algorithm is proposed to train the speech...
متن کاملA GPU-Adapted Structure for Unstructured Grids
A key advantage of working with structured grids (e.g., images) is the ability to directly tap into the powerful machinery of linear algebra. This is not much so for unstructured grids where intermediate bookkeeping data structures stand in the way. On modern high performance computing hardware, the conventional wisdom behind these intermediate structures is further challenged by costly memory ...
متن کاملA sparse H-matrix arithmetic: general complexity estimates
In a preceding paper (Hackbusch, Computing 62 (1999) 89–108), a class of matrices (H-matrices) has been introduced which are data-sparse and allow an approximate matrix arithmetic of almost linear complexity. Several types ofH-matrices have been analysed in Hackbusch (Computing 62 (1999) 89–108) and Hackbusch and Khoromskij (Preprint MPI, No. 22, Leipzig, 1999; Computing 64 (2000) 21–47) which ...
متن کاملAutomatically Tuning Sparse Matrix-Vector Multiplication for GPU Architectures
Graphics processors are increasingly used in scientific applications due to their high computational power, which comes from hardware with multiple-level parallelism and memory hierarchy. Sparse matrix computations frequently arise in scientific applications, for example, when solving PDEs on unstructured grids. However, traditional sparse matrix algorithms are difficult to efficiently parallel...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- IJPEDS
دوره 22 شماره
صفحات -
تاریخ انتشار 2007