Configurable computing has become a subject of a great deal of research given its potential to greatly accelerate a wide variety of applications that require high throughput. In this context, the dataflow approach is still promising to accelerate the kernel of applications in the field of HPC. That tanks to a computational dataflow engine able to execute dataflow program graphs directly in a custom hardware. On the other hand, evaluating radically different models of computation remains yet an open issue. In this paper we present as case study the matrix multiplication that constitutes the fundamental kernel of the linear algebra. The evaluation takes into account the execution of the matrix product both in non-pipelined and pipelined modes...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Modern graphics processing units (GPUs) have been at the leading edge of in-creasing chip-level para...
UnrestrictedThe large capacity of field programmable gate arrays (FPGAs) has prompted researchers to...
Configurable computing has become a subject of a great deal of research given its potential to great...
Matrix operations, like matrix multiplication, are commonly used in almost all areas of scientific r...
In this paper we draw our attention to several algorithms for the dataflow computer paradigm, where ...
Achieving high-performance while reducing power consumption is the key question as tech-nology scali...
Floating-point matrix multiplication is a basic kernel in scientific computing. It has been shown th...
The dissemination of multi-core architectures and the later irruption of massively parallel devices,...
The Process-Oriented Dataflow System (PODS) is an execution model that combines the von Neumann and ...
Our goal is to devise a computer comprising large numbers of cooperating processors (LSI). In doing ...
Our goal is to devise a computer comprising large numbers of cooperating processors (LSI). In doing ...
Matrix multiplication is required for a wide variety of applications, including data mining, linear ...
To solve the computational complexity and time-consuming problem of large matrix multiplication, thi...
In this article the authors develop some algorithms and tools for solving matrix problems on paralle...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Modern graphics processing units (GPUs) have been at the leading edge of in-creasing chip-level para...
UnrestrictedThe large capacity of field programmable gate arrays (FPGAs) has prompted researchers to...
Configurable computing has become a subject of a great deal of research given its potential to great...
Matrix operations, like matrix multiplication, are commonly used in almost all areas of scientific r...
In this paper we draw our attention to several algorithms for the dataflow computer paradigm, where ...
Achieving high-performance while reducing power consumption is the key question as tech-nology scali...
Floating-point matrix multiplication is a basic kernel in scientific computing. It has been shown th...
The dissemination of multi-core architectures and the later irruption of massively parallel devices,...
The Process-Oriented Dataflow System (PODS) is an execution model that combines the von Neumann and ...
Our goal is to devise a computer comprising large numbers of cooperating processors (LSI). In doing ...
Our goal is to devise a computer comprising large numbers of cooperating processors (LSI). In doing ...
Matrix multiplication is required for a wide variety of applications, including data mining, linear ...
To solve the computational complexity and time-consuming problem of large matrix multiplication, thi...
In this article the authors develop some algorithms and tools for solving matrix problems on paralle...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Modern graphics processing units (GPUs) have been at the leading edge of in-creasing chip-level para...
UnrestrictedThe large capacity of field programmable gate arrays (FPGAs) has prompted researchers to...