If I still did research full time I'd probably get a Xeon workstation loaded with RAM for home. But it's just a hobby for me now that my day job is writing non-scientific software, so it doesn't seem like a justifiable expense. Might go up from my current 4 cores and 32 GB to something Zen-based later this year.

(Tangentially: I wouldn't bother with ECC RAM for this application unless that were required by the rest of the hardware. Memory errors may slightly affect time to a converged solution, but it's rare that a flipped bit would actually cause a job to converge to a different solution.)

If this is just a hobby why not rent a large VM from us (GCE) or AWS? It sounds like you don't run enough to want a box for anything like 24x7, but that it'd be great to have tons of memory and lots of cores (or a giant SSD). We just announced our Skylakes yesterday ;).

Disclosure: I work on Google Cloud,

I work on NLP projects and have similar issue with memory.

The reason I don't use cloud computing is that you constantly have to worry about moving data around, turning stuff on and off, API changes, data movement costs, product lineup changes (should I store this stuff on S3 or local HD), locally compiling all your stuff again or containerization and associated time overhead.

Local large box makes way more sense if you're doing solo projects. And if traveling, it would way more sense to rent a VPS from Hetzner. Flat cost structure and tons of bang for the buck.

BTW, I you can get 128 gb LGA2011-v3 motherboards.

https://www.newegg.com/Product/Product.aspx?Item=N82E1681315...

and it seems like it works: http://www.pcworld.com/article/2938855/hardcore-hardware-we-...

even though the spec says max 64gb: https://ark.intel.com/products/82932/Intel-Core-i7-5820K-Pro...

I can confirm, I run machine learning workloads on a home machine with 128GB of RAM on an X99-E WS/USB 3.1 motherboard. My manual explicitly states that it has 128GB RAM support, as well.