SLAM is a fundamental problem in robotics that can be solved by a set of algorithms that are known to have large computational complexity. GraphSLAM contains a rapidly growing system of equations which are often solved by sparse evaluation techniques. This paper proposes a technique to evaluate sparse equations on an FPGA by restricting the maximum amount of items in the system. The implementation is done using CλaSH which allows a transformation from mathematical descriptions to a hardware design. The results show a scalable hardware design that can be used to solve small and large systems with dynamic parallelism
Power flow computation is ubiquitous in the operation and planning of power systems.\ud Traditional ...
Cholesky factorization is a fundamental problem in most engineering and science computation applicat...
The original publication is available at www.springerlink.comInternational audienceA wide class of g...
The Finite Element Method (FEM) is a computationally intensive scientific and engineering analysis t...
UnrestrictedThe large capacity of field programmable gate arrays (FPGAs) has prompted researchers to...
One of the key kernels in scientific applications is the Sparse Matrix Vector Multiplication (SMVM)....
As part of our effort to parallelise SPICE simulations over multiple FPGAs, we present a parallel FP...
The widespread adoption of massively parallel processors over the past decade has fundamentally tran...
FPGA-based soft processors customized for operations on sparse graphs can deliver significant perfor...
Solving Linear Equation System (LESs) is a common problem in numerous fields of science. Even though...
The Finite Element Method (FEM) is a computationally intensive scientific and engineering analysis t...
As field-programmable gate array (FPGA) capacities continue to increase in lockstep with semiconduct...
Abstract. Motivated by the goal of factoring large integers using the Number Field Sieve, several sp...
International audienceThis article presents dedicated hardware arithmetic operators for function eva...
Many important applications are organized around long-lived, irregular sparse graphs (e.g., data an...
Power flow computation is ubiquitous in the operation and planning of power systems.\ud Traditional ...
Cholesky factorization is a fundamental problem in most engineering and science computation applicat...
The original publication is available at www.springerlink.comInternational audienceA wide class of g...
The Finite Element Method (FEM) is a computationally intensive scientific and engineering analysis t...
UnrestrictedThe large capacity of field programmable gate arrays (FPGAs) has prompted researchers to...
One of the key kernels in scientific applications is the Sparse Matrix Vector Multiplication (SMVM)....
As part of our effort to parallelise SPICE simulations over multiple FPGAs, we present a parallel FP...
The widespread adoption of massively parallel processors over the past decade has fundamentally tran...
FPGA-based soft processors customized for operations on sparse graphs can deliver significant perfor...
Solving Linear Equation System (LESs) is a common problem in numerous fields of science. Even though...
The Finite Element Method (FEM) is a computationally intensive scientific and engineering analysis t...
As field-programmable gate array (FPGA) capacities continue to increase in lockstep with semiconduct...
Abstract. Motivated by the goal of factoring large integers using the Number Field Sieve, several sp...
International audienceThis article presents dedicated hardware arithmetic operators for function eva...
Many important applications are organized around long-lived, irregular sparse graphs (e.g., data an...
Power flow computation is ubiquitous in the operation and planning of power systems.\ud Traditional ...
Cholesky factorization is a fundamental problem in most engineering and science computation applicat...
The original publication is available at www.springerlink.comInternational audienceA wide class of g...