Multi-dimensional Sparse Matrix Storage

نویسندگان

  • Jiri Dvorský
  • Michal Krátký
چکیده

Large sparse matrices play important role in many modern information retrieval methods. These methods, such as clustering, latent semantic indexing, performs huge number of computations with such matrices, thus their implementation should be very carefully designed. In this paper we discuss three implementations of sparse matrices. The first one is classical, based on lists. The second is previously published approach based on quadrant trees. The multi-dimensional approach is extended and usage of general multi-dimensional structure for sparse matrix storage is introduced in this paper.

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 Data Compression Methods for Multi-Dimensional Sparse Array Operations

For sparse array operations, in general, the sparse arrays are compressed by some data compression schemes in order to obtain better performance. The Compressed Row/Column Storage (CRS/CCS) schemes are the two common used data compression schemes for sparse arrays in the traditional matrix representation (TMR). When extended to higher dimensional sparse arrays, array operations used the CRS/CCS...

متن کامل

The TileDB Array Data Storage Manager

We present a novel storage manager for multi-dimensional arrays that arise in scientific applications, which is part of a larger scientific data management system called TileDB. In contrast to existing solutions, TileDB is optimized for both dense and sparse arrays. Its key idea is to organize array elements into ordered collections called fragments. Each fragment is dense or sparse, and groups...

متن کامل

Utilizing Recursive Storage in Sparse Matrix-Vector Multiplication - Preliminary Considerations

Computations with sparse matrices on “multicore cache based” computers are affected by the irregularity of the problem at hand, and performance degrades easily. In this note we propose a recursive storage format for sparse matrices, and evaluate its usage for the Sparse Matrix-Vector (SpMV) operation on two multicore and one multiprocessor machines. We report benchmark results showing high perf...

متن کامل

Range Top/Bottom k Queries in OLAP Sparse Data Cubes

A range top k query finds the top k maximum values over all selected cells of an OLAP data cube where the selection is specified by the range of contiguous values for each dimension. In this paper, we propose a partitionbased storage structure, which is capable of answering both range top and bottom k queries in OLAP sparse data cubes. This is achieved by partitioning a multi-dimensional sparse...

متن کامل

Rapid Near-Neighbor Interaction of High-dimensional Data via Hierarchical Clustering

Calculation of near-neighbor interactions among high dimensional, irregularly distributed data points is a fundamental task to many graph-based or kernel-based machine learning algorithms and applications. Such calculations, involving large, sparse interaction matrices, expose the limitation of conventional data-and-computation reordering techniques for improving space and time locality onmoder...

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 2004