We introduce a 64-bit ANSI/IEEE Std 754-1985 floating point design of a hardware matrix multiplier optimized for FPGA implementations. A general block matrix multiplication algorithm, applicable for an arbitrary matrix size is proposed. The algorithm potentially enables optimum performance by exploiting the data locality and reusability incurred by the general matrix multiplication scheme and considering the limitations of the I/O bandwidth and the local storage volume. We implement a scalable linear array of processing elements (PE) supporting the proposed algorithm in the Xilinx Virtex II Pro technology. Synthesis results confirm a superior performance-area ratio compared to related recent works. Assuming the same FPGA chip, the same amou...
The design of a floating point matrix- vector multiplication processor array for VLSI, which has an ...
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...
We present two designs (I and II) for IEEE 754 double precision floating point matrix multiplication...
We present two designs (I and II) for IEEE 754 double precision floating point matrix multiplication...
Abstract — In this paper, we introduce a scalable macro-pipelined architecture to perform floating p...
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...
Matrix multiplication is required for a wide variety of applications, including data mining, linear ...
Matrix multiplication is a computation intensive operation and plays an important role in many scien...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Floating-point matrix multiplication is a basic kernel in scientific computing. It has been shown th...
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright...
Part 4: Architecture and HardwareInternational audienceMatrix computing plays a vital role in many s...
The design of a floating point matrix- vector multiplication processor array for VLSI, which has an ...
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...
We present two designs (I and II) for IEEE 754 double precision floating point matrix multiplication...
We present two designs (I and II) for IEEE 754 double precision floating point matrix multiplication...
Abstract — In this paper, we introduce a scalable macro-pipelined architecture to perform floating p...
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...
Matrix multiplication is required for a wide variety of applications, including data mining, linear ...
Matrix multiplication is a computation intensive operation and plays an important role in many scien...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
Floating-point matrix multiplication is a basic kernel in scientific computing. It has been shown th...
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright...
Part 4: Architecture and HardwareInternational audienceMatrix computing plays a vital role in many s...
The design of a floating point matrix- vector multiplication processor array for VLSI, which has an ...
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...