Bill,

to answer the general part of you question, there are quite a few packages that 
allow you to use your GPU. At the low level you can use OpenCL which allows you 
to write code directly on the GPU and turn it into R functions. At a higher 
level there are frameworks like Torch and Tensorflow that support GPUs and 
there are packages like keras or rTorch that provide interfaces to that, e.g. 
for machine learning models. All those support Apple silicon GPUs.

However, you mentioned bigCor which is orthogonal to that. There are papers 
(such as https://doi.org/10.1134/S1995080219050068 ) that describe some 
approaches to using GPUs to compute covariance matrices, but in general GPUs 
don't really give you a large benefit on their own since it is a lot more about 
memory management and using smart algorithms/data structures to reduce the 
necessary computation. You may have more luck asking in HPC forums about that 
since is not really Mac-specifc (and the answer may depend on what you are 
actually trying to do so may need more details).

Cheers,
Simon


> On 22/02/2023, at 6:12 AM, William R Revelle <reve...@northwestern.edu> wrote:
> 
> Dear R-Mac users.
> 
> In trying to speed up a large correlation problem (600K subjects, 6k 
> variables,)  which I can do using my bigCor function, I decided it was time 
> to learn how to use GPU on my Mac book with its M1 Max gpu.  
> 
> Having spent a day searching the web and trying  various approaches, I give 
> up.
> 
> Are there any packages I can use to do calculations on the GPU part of my Mac 
> using R?
> 
> Thanks.
> 
> Bill
> 
> William Revelle                  personality-project.org/revelle.html
> Professor                               personality-project.org
> Department of Psychology www.wcas.northwestern.edu/psych/
> Northwestern University          www.northwestern.edu/
> Use R for psychology         personality-project.org/r
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