Libreoffice has OpenCL acceleration for some spreadsheet operations. With the advent of NVME storage, and the potential bandwidth it yields, I would expect to see database systems emerging that can GPGPU accelerate operations on tables to be way, way faster than what a CPU can handle.
> I would expect to see database systems emerging that can GPGPU accelerate operations on tables to be way, way faster than what a CPU can handle.
Why do you expect that? Many DBMS operations that are not I/O limited are memory limited, and a GPU does not help you there (on the contrary, you get another bottleneck in data transfers to the small GPU memory). What can help is better data organization, e.g. transposed (columnar) storage.
People use spreadsheets for anything that you'd use a "normal" programming language for. When I worked at a bank, a real-time trading system was implemented as an Excel spreadsheet. There were third-party and internally-developed libraries to do the complicated stuff (multicast network protocols, complicated calculations that needed to be the same across all implementations, etc.) but the bulk of the business logic and UI were Excel. It's easy to modify, extend, and play with... which also makes it easy to break functionality and introduce subtle bugs. Though the same is true of any software development environment -- things you don't test break.
Don't think of spreadsheets as glorified tables. Think of them as the world's most-commonly used business logic and statistical programming language. A competitor to R, if you will.
Statistics, sure, that's definitely a good candidate for GPUs. I don't know much about R, but a quick google suggests you can run R code on a GPU, by working with certain object types, like matrices with GPU-accelerated operations.
That doesn't seem like it maps very well to a spreadsheet unless you have one big matrix per cell. I'm guessing (maybe incorrectly) that when people work with matrices in Excel, they're spread across a grid of cells. You probably could detect matrix-like operations and convert them to GPU batch jobs, but it seems very hard and I'm skeptical of how much you'd gain.
So I'm still wondering what kinds of typical Excel tasks are amenable to GPU acceleration in the first place. People use Excel to do a lot of surprising things, sure. But people use C++ and Python and Javascript for a lot of things too, and you can't just blithely move those over to the GPU.
Maybe it's specific expensive operations, like "fit a curve to the data in this huge block of cells"?
I'm aware of big spreadsheets, but from what I've seen, it tends to be complex and very ad-hoc calculations that (I imagine) don't lend themselves very well to GPUs.
Making very complex tasks run well on a GPU is hard, whereas CPUs are great for dealing with that stuff.
If you have something like a 100,000 row spreadsheet where every row is doing exactly the same calculation on different input data, sure, that starts to make sense. If people are really doing that in Excel, I'm surprised! (but maybe I shouldn't be)
