cburdick2

3 ms·

1. 1.▲
   by cburdick2 4y ago

   That's true, but for those types of applications you're looking at a custom ASIC in most cases. high ns or very low us are FPGA territory, and low us and above are suitable on GPU.
2. 2.▲
   by cburdick2 4y ago

   PCI cost is typically in the noise for realistic applications. There are ways to reduce latency and signal flags across PCIe, but do most of the workload on GPU to keep the latency down.
3. 3.▲
   by cburdick2 4y ago

   I think you'd need to qualify what better means here. GPUs will give much higher performance for FP64 than CPUs will. The price of CPUs has continued to increase significantly in the last 5 years, and now high-end Xeons are more expens
4. 4.▲
   by cburdick2 4y ago

   No, but also consider that it's a pretty new project and is heavily based on Nvidia math libraries. some of these libraries don't have exact counterparts on the amd side.
5. 5.▲
   by cburdick2 4y ago

   For GPU support take a look at our library: https://github.com/NVIDIA/MatX If anything is missing we're happy to take feature requests.
6. 6.▲
   by cburdick2 4y ago

   If blaze is of interest to you and you use GPUs, check out our library called MatX: https://github.com/NVIDIA/MatX I haven't used blaze, but the readme sounds similar. We generate kernels using expression template