As microprocessors increase in power, the economics of centralized computing has changed dramatically. At the beginning of the 1980's, mainframes and super computers were often considered to be cost-effective machines for scalar computing. Today, microprocessor-based RISC (reduced-instruction-set computer) systems have displaced many uses of mainframes and supercomputers. Supercomputers are still cost competitive when processing jobs that require both large memory size and high memory bandwidth. One such application is array processing. Certain numerical operations are appropriate to use in a Remote Procedure Call (RPC)-based environment. Matrix multiplication is an example of an operation that can have a sufficient number of arithmetic ope...
With diminishing performance improvement from general-purpose processors and reducing cost for prog...
Problems which can arise with vector and parallel computers are discussed in a user oriented context...
Abstract. Traditional parallel programming methodologies for improv-ing performance assume cache-bas...
A considerable volume of large computational computer codes were developed for NASA over the past tw...
Array processors have been used extensively in military applications involving sonar and radar signa...
Using super-resolution techniques to estimate the direction that a signal arrived at a radio receive...
Thesis (Ph.D.), School of Electrical Engineering and Computer Science, Washington State UniversityPa...
This paper presents an approach to increasing the capability of scientific computing through the use...
KFA Jülich is one of the largest big-science research centers in Europe. At KFA, computational scien...
Some level-2 and level-3 Distributed Basic Linear Algebra Subroutines (DBLAS) that have been impleme...
Strassen’s matrix multiplication reduces the computational cost of multiplying matrices of size n × ...
Highly parallel computing architectures are the only means to achieve the computation rates demanded...
The Advanced Scientific Computers Project of Argonne's Applied Mathematics Division has two objectiv...
Computing is seeing an unprecedented improvement in performance; over the last five years there has ...
The multiplication of large spare matrices is a basic operation for many scientific and engineering ...
With diminishing performance improvement from general-purpose processors and reducing cost for prog...
Problems which can arise with vector and parallel computers are discussed in a user oriented context...
Abstract. Traditional parallel programming methodologies for improv-ing performance assume cache-bas...
A considerable volume of large computational computer codes were developed for NASA over the past tw...
Array processors have been used extensively in military applications involving sonar and radar signa...
Using super-resolution techniques to estimate the direction that a signal arrived at a radio receive...
Thesis (Ph.D.), School of Electrical Engineering and Computer Science, Washington State UniversityPa...
This paper presents an approach to increasing the capability of scientific computing through the use...
KFA Jülich is one of the largest big-science research centers in Europe. At KFA, computational scien...
Some level-2 and level-3 Distributed Basic Linear Algebra Subroutines (DBLAS) that have been impleme...
Strassen’s matrix multiplication reduces the computational cost of multiplying matrices of size n × ...
Highly parallel computing architectures are the only means to achieve the computation rates demanded...
The Advanced Scientific Computers Project of Argonne's Applied Mathematics Division has two objectiv...
Computing is seeing an unprecedented improvement in performance; over the last five years there has ...
The multiplication of large spare matrices is a basic operation for many scientific and engineering ...
With diminishing performance improvement from general-purpose processors and reducing cost for prog...
Problems which can arise with vector and parallel computers are discussed in a user oriented context...
Abstract. Traditional parallel programming methodologies for improv-ing performance assume cache-bas...