Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Contact submission #19

Open
markotoplak opened this issue Apr 24, 2020 · 5 comments
Open

Contact submission #19

markotoplak opened this issue Apr 24, 2020 · 5 comments

Comments

@markotoplak
Copy link
Contributor

Submitter: Oleksandr Gakh
It is rather hardware question than technical problem. I have noticed that I can analyze spectral data much faster on Mac computer (Xeon processor, RAM 64GB) then on PC (Xeon processor, RAM 128GB). Thus, is there any specific requirements for hardware set up for faster performance (processor, RAM, video card configuration etc). Thank you

@markotoplak
Copy link
Contributor Author

Could you share some measurements with us? Are there any particular operations that are slower on Windows? What did you use for installation? Packages from the web site or manual/pip installation?

Whenever I saw such differences before, it was due to different libraries used for matrix operations (different libraries within numpy; they are system dependent). The difference between a slow and a fast matrix library can ~10x for matrix multiplication, but I think, that nowdays all numpy distributions are well optimized.

@AlexGakh
Copy link

Hi Marko, I do process the data from FTIR microscope and on PC it is slow from the beginning, even when I download the data, and each step of following analysis (visualization, baseline normalization etc). I have monitored the usage of memory (the PC has 128GB) and it has been used of 30-40% of full capacity. For installation I have used Quasar-0.7.1-Miniconda-x86_64.exe file and I just follow instructions, whale on Mac it was installed an older version of Orange through anaconda navigator. So, if there is a problems with libraries how I can check and change it in order to optimize the analysis. Please, let me know if you need more information, thank you, Alex.

@AlexGakh
Copy link

AlexGakh commented May 2, 2020

One more question is Quasar better works with CUDA or OpenGL graphic cards? The reason why I am asking that the PC which works slow have the NVIDIA graphic card (Cuda) while the Mac have FirePro (OpenGL).

@stuart-cls
Copy link
Member

For the GPU, we don't have any GPU-accelerated calculations that I'm aware of at this time.

For the CPU, I think you should be using a recent Intel MKL (vector math library) since you used the Quasar installer. You can confirm by running "Quasar Command Prompt" and entering conda list mkl. Mine shows mkl with version 2019.4. I think MKL is the fastest library on Windows.

@AlexGakh
Copy link

AlexGakh commented May 5, 2020 via email

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants