National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Heat Diffusion Simulation on GPU
Hradecký, Michal ; Vašíček, Zdeněk (referee) ; Jaroš, Jiří (advisor)
This thesis deals with the simulation of heat diffusion in human tissues. The proposed algorithm uses a finite-difference time-domain method, which is applied on the governing equation describing the system. A modern graphics card is used to accelerate the simulation. The performance achieved on the GPU card is compared with the implementation exploiting a modern multicore CPU. The output of this thesis is a set of differently optimized algorithms targeted on NVIDIA graphics cards. The experimental results reveal that the use of shared memory is contraproductive and the best performance is achieved by a register based implementation. The overall speedup of 18.5 was reached when comparing a NVIDIA GeForce GTX 580 with a quad-core Intel Core i7 920 CPU. This nicely corresponds with the theoretical capabilities of  both architectures.
Heat Diffusion Simulation on GPU
Hradecký, Michal ; Vašíček, Zdeněk (referee) ; Jaroš, Jiří (advisor)
This thesis deals with the simulation of heat diffusion in human tissues. The proposed algorithm uses a finite-difference time-domain method, which is applied on the governing equation describing the system. A modern graphics card is used to accelerate the simulation. The performance achieved on the GPU card is compared with the implementation exploiting a modern multicore CPU. The output of this thesis is a set of differently optimized algorithms targeted on NVIDIA graphics cards. The experimental results reveal that the use of shared memory is contraproductive and the best performance is achieved by a register based implementation. The overall speedup of 18.5 was reached when comparing a NVIDIA GeForce GTX 580 with a quad-core Intel Core i7 920 CPU. This nicely corresponds with the theoretical capabilities of  both architectures.

Interested in being notified about new results for this query?
Subscribe to the RSS feed.