A Simple Riemann Solver and High-Order Godunov Schemes for Hyperbolic Systems of Conservation Laws

1995 ◽  
Vol 121 (1) ◽  
pp. 51-65 ◽  
Author(s):  
Wenlong Dai ◽  
Paul R. Woodward
Keyword(s):  
Conservation Laws ◽  
Hyperbolic Systems ◽  
High Order ◽  
Riemann Solver ◽  
Systems Of Conservation Laws

scholarly journals A Hybrid Riemann Solver for Large Hyperbolic Systems of Conservation Laws

2017 ◽  
Vol 39 (6) ◽  
pp. A2911-A2934 ◽  
Author(s):  
Birte Schmidtmann ◽  
Manuel Torrilhon
Keyword(s):  
Conservation Laws ◽  
Hyperbolic Systems ◽  
Riemann Solver ◽  
Systems Of Conservation Laws

On the arithmetic intensity of high-order finite-volume discretizations for hyperbolic systems of conservation laws

2017 ◽  
Vol 33 (1) ◽  
pp. 25-52 ◽  
Author(s):  
J Loffeld ◽  
JAF Hittinger
Keyword(s):  
Conservation Laws ◽  
Finite Volume ◽  
Hyperbolic Systems ◽  
Finite Volume Methods ◽  
High Order ◽  
Floating Point ◽  
Systems Of Conservation Laws ◽  
Data Transfers ◽  
Blue Gene ◽  
Theory And Experiments

It has been conjectured that higher-order discretizations for partial differential equations will have advantages over the lower-order counterparts commonly used today. The reasoning is that the increase in arithmetic operations will be more than offset by the reduction in data transfers and the increase in concurrent floating-point units. To evaluate this conjecture, the arithmetic intensity of a class of high-order finite-volume discretizations for hyperbolic systems of conservation laws is theoretically analyzed for spatial discretizations from orders three through eight in arbitrary dimensions. Three cache models are considered: the limiting cases of no cache and infinite cache as well as a finite-sized cache model. Models are validated experimentally by measuring floating-point operations and data transfers on an IBM Blue Gene/Q node. Theory and experiments demonstrate that high-order finite-volume methods will be able to provide increases in arithmetic intensity that will be necessary to make better utilization of on-node floating-point capability.

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