Computations involving matrices form the kernel of a large spectrum of computationally demanding applications for which FPGAs have actively been utilized as accelerators. The performances of such matrix operations on FPGAs are related to underlying architectural parameters such as computational resources, memory and I/O bandwidth. A model that gives bounds on the peak performance of matrix-vector and matrix-matrix multiplication operations on FPGAs based on these parameters is presented. The architecture and efficiency of existing implementations are compared against the model. Future trends in matrix performance on FPGA devices are estimated based on the performance model and system parameters from the past decade. © 2011 IEEE.published_o...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Part 4: Architecture and HardwareInternational audienceMatrix computing plays a vital role in many s...
We introduce a 64-bit ANSI/IEEE Std 754-1985 floating point design of a hardware matrix multiplier o...
Computations involving matrices form the kernel of a large spectrum of computationally demanding app...
Matrix multiplication is at the core of high-performance numerical computation. Software methods of ...
Floating-point matrix multiplication is a basic kernel in scientific computing. It has been shown th...
We present two designs (I and II) for IEEE 754 double precision floating point matrix multiplication...
Matrix operations, like matrix multiplication, are commonly used in almost all areas of scientific r...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Field Programmable Gate Arrays (FPGAs) enable powerful performance acceleration for scientific compu...
We present two designs (I and II) for IEEE 754 double precision floating point matrix multiplication...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
To solve the computational complexity and time-consuming problem of large matrix multiplication, thi...
To solve the computational complexity and time-consuming problem of large matrix multiplication, thi...
Matrix multiplication is required for a wide variety of applications, including data mining, linear ...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Part 4: Architecture and HardwareInternational audienceMatrix computing plays a vital role in many s...
We introduce a 64-bit ANSI/IEEE Std 754-1985 floating point design of a hardware matrix multiplier o...
Computations involving matrices form the kernel of a large spectrum of computationally demanding app...
Matrix multiplication is at the core of high-performance numerical computation. Software methods of ...
Floating-point matrix multiplication is a basic kernel in scientific computing. It has been shown th...
We present two designs (I and II) for IEEE 754 double precision floating point matrix multiplication...
Matrix operations, like matrix multiplication, are commonly used in almost all areas of scientific r...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Field Programmable Gate Arrays (FPGAs) enable powerful performance acceleration for scientific compu...
We present two designs (I and II) for IEEE 754 double precision floating point matrix multiplication...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
To solve the computational complexity and time-consuming problem of large matrix multiplication, thi...
To solve the computational complexity and time-consuming problem of large matrix multiplication, thi...
Matrix multiplication is required for a wide variety of applications, including data mining, linear ...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Part 4: Architecture and HardwareInternational audienceMatrix computing plays a vital role in many s...
We introduce a 64-bit ANSI/IEEE Std 754-1985 floating point design of a hardware matrix multiplier o...