> Each version is severely memory bandwidth bottlenecked, the CUDA version suffers the most with its practical 11.8 GB/s device-to-host bandwidth due to its PCI-Express 3.0 x16 interface.
> GeForce GTX 1050 Ti with Max-Q Design (PCIe 3.0 x16) (2016)
> Intel Core i5-8300H (2020)
This is a low-price 8 year old GPU and a 4 year old CPU. And he seems to be including loading the data to GPU. Newer cards have wide PCIe 5.0 or some faster interconnect, like Nvidia Grace-Hopper.
Also he is comparing his own CUDA implementation. He should use one of the many available in CUBLAS/CUTLASS. Making a good CUDA GEMM is a very difficult art and very hardware specific
PCIe 3.0? What?
https://cowfreedom.de/#appendix/computer_specs/
> GeForce GTX 1050 Ti with Max-Q Design (PCIe 3.0 x16) (2016)
> Intel Core i5-8300H (2020)
This is a low-price 8 year old GPU and a 4 year old CPU. And he seems to be including loading the data to GPU. Newer cards have wide PCIe 5.0 or some faster interconnect, like Nvidia Grace-Hopper.
Also he is comparing his own CUDA implementation. He should use one of the many available in CUBLAS/CUTLASS. Making a good CUDA GEMM is a very difficult art and very hardware specific