International audienceThis paper introduces methods for extending the classical systolic synthesis methodology to multi-dimensional time which implies the use of memories in the resulting architecture. Memory functions are used to define where the data are stored during execution, the targeted architecture is a distributed memory VLSI circuit. We describe a structural VHDL program for the matrix multiplication algorithm synthesised for a FPGA platform using these design principles. Our results show that the complexity added in each processor by the memories and the control is moderate and justifies in practice the use of such architectures
Abstract. Real-time signal processing requires fast computation ofinner products. Distributed arithm...
In today's heterogenous computing world, field-programmable gate arrays (FPGA) represent the energy-...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
International audienceThis paper introduces methods for extending the classical systolic synthesis m...
Abstract — This paper introduces methods for extending the classical systolic synthesis methodology ...
Matrix operations, like matrix multiplication, are commonly used in almost all areas of scientific r...
Due to advances in VLSI technology, it is possible to implement complex digital systems on a single ...
This thesis deals with ways to describe hardware. It presents the methods used in the synthesis of t...
Parallel and systolic structures for matrix algebra algorithms have been around for quite a long tim...
We present a high-level synthesis framework to synthesize optimized hardware on FPGAs from algorithm...
Previous research has shown that the performance of any computation is directly related to the archi...
Several system-on-chip (SoC) platforms have recently emerged that use reconfigurable logic (FPGAs) a...
Multiplication is most commonly used operation in mathematics. Integer multiplication is used common...
This paper presents a hardware-efficient memory allocation technique, called EMA, that detects the e...
Regular arrays, particularly systolic arrays, have been the subject of continuous interest for the p...
Abstract. Real-time signal processing requires fast computation ofinner products. Distributed arithm...
In today's heterogenous computing world, field-programmable gate arrays (FPGA) represent the energy-...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...
International audienceThis paper introduces methods for extending the classical systolic synthesis m...
Abstract — This paper introduces methods for extending the classical systolic synthesis methodology ...
Matrix operations, like matrix multiplication, are commonly used in almost all areas of scientific r...
Due to advances in VLSI technology, it is possible to implement complex digital systems on a single ...
This thesis deals with ways to describe hardware. It presents the methods used in the synthesis of t...
Parallel and systolic structures for matrix algebra algorithms have been around for quite a long tim...
We present a high-level synthesis framework to synthesize optimized hardware on FPGAs from algorithm...
Previous research has shown that the performance of any computation is directly related to the archi...
Several system-on-chip (SoC) platforms have recently emerged that use reconfigurable logic (FPGAs) a...
Multiplication is most commonly used operation in mathematics. Integer multiplication is used common...
This paper presents a hardware-efficient memory allocation technique, called EMA, that detects the e...
Regular arrays, particularly systolic arrays, have been the subject of continuous interest for the p...
Abstract. Real-time signal processing requires fast computation ofinner products. Distributed arithm...
In today's heterogenous computing world, field-programmable gate arrays (FPGA) represent the energy-...
In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and ef...