. Applying fast scientific computing algorithms to large problems presents a difficult engineering problem. We describe a novel architecture for addressing this problem that uses a robust client-server model for interactive large-scale linear algebra computation. We discuss competing approaches and demonstrate the relative strengths of our approach. By way of example, we describe MITMatlab, a powerful transparent client interface to the linear algebra server. With MITMatlab, it is now straightforward to implement full-blown algorithms intended to work on very large problems while still using the powerful interactive and visualization tools that Matlab provides. We also examine the efficiency of our model by timing selected operations and comparing them to commonly used approaches. 1 Introduction We describe a novel architecture for a "linear algebra server" that operates on very large matrices. Matrices are created by the server and distributed across many machines or processors. Oper...

This paper describes MITMatlab, a system that enables users of supercomputers to transparently work on large data sets within Matlab. MITMatlab communicates with an external server that is responsible for storing and operating on the data. Through the use of Matlab's object oriented features, we can handle this data as though it were "in" Matlab. For example, we can type [u,s,v] = svds(a,5) in Matlab and get results regardless of whether the matrix a has fifty or fifty million non-zero elements. We present the structure and details of our implementation along with some examples showing MITMatlab in action. 1 Introduction This paper describes MITMatlab, a system that enables users of supercomputers to work in parallel transparently on large data sets within Matlab. MITMatlab is based on the Parallel Problems Server (PPServer)[8], a standalone linear algebra server that provides a mechanism for executing distributed memory algorithms on large data sets. This work is motivated by the des...

This paper describes MITMatlab, a system that enables users of supercomputers to transparently work on large data sets within Matlab. MITMatlab communicates with an external server that is responsible for storing and operating on the data. Through the use of Matlab's object oriented features, we can handle this data as though it were "in" Matlab. For example, we can type [u,s,v] = svds(a,5) in Matlab and get results regardless of whether the matrix a has fifty or fifty million non-zero elements. We present the structure and details of our implementation along with some examples showing MITMatlab in action. 1 Introduction This paper describes MITMatlab, a system that enables users of supercomputers to work in parallel transparently on large data sets within Matlab. MITMatlab is based on the Parallel Problems Server (PPServer)[8], a standalone linear algebra server that provides a mechanism for executing distributed memory algorithms on large data sets. This work is motivated by...

This paper describes MITMatlab, a system that enables users of supercomputers to transparently work on large data sets within Matlab. MITMatlab communicates with an external server that is responsible for storing and operating on the data. Through the use of Matlab's object oriented features, we can handle this data as though it were "in" Matlab. For example, we can type [u,s,v] = svds(a,5) in Matlab and get results regardless of whether the matrix a has fifty or fifty million non-zero elements.