Seems unlikely; the link is quite dated (before the news about 12nm ttbomr). The process improvement would allow for more efficient server parts, and thus higher margin models.https://semiaccurate.com/2017/05/17/amds-details-epyc-server-ambitions/
EPYC will remain on 14LPP . Ryzen and most likely ThreadRipper will get a update on 12LP as it really needs higher clock frequency to compete with Coffeelake. Since Pinnacle Ridge dies are desktop only AMD could tweak fabric speeds specifically for reducing memory latency and improving gaming performance.
Keep in mind that GF isn't that far away from offering 7nm LP. Epyc can make the jump to that node without there being much time between releases.Seems unlikely; the link is quite dated (before the news about 12nm ttbomr). The process improvement would allow for more efficient server parts, and thus higher margin models.
It'd be surprising to see PR as a very different part from SR---for example SR with all the server uncore area removed, shrunk (by nr of transistors and by higher density) as a pure desktop product, 8c/16t in a very small area like <140mm2. Maybe it'd even make sense. I'd be very surprised to see this happen though.
I've looked into Darktable, but the problem with it is that using CPU for the processing is pretty much pointless.Maybe RAW image processing using Darktable (it is Windows compatible now).
I did it in the original review.Can you compare multi-threaded IPC with *and* without SMT? Wondering how much of AMD's MT (scaling) advantage is down to SMT.
From the looks of it, it would be too time consuming to test and hard to maintain unfortunately@The Stilt , Could you use Julia (Programming Language)?
You can create many great tests using it.
You can start with - Benchmark MATLAB & Julia for Matrix Operations.
Also using the Image Package one could test many Image Processing procedures.
Another option is LuaJIT with SciLua (Performance for JIT languages is very interesting).
On the project frontage you'll be able to find a built in test.
Actually since SMT helps hide latency, I expect SMT yield to drop a bit with Raven and Pinnacle Ridge due to the latency reductions in both caches and memory.I did it in the original review.
Based on the changes I don't think there is reason to expect that the SMT yield has changed in either way in the newer Zen iterations.
I could double check with few tests, but generally I don't think there is any difference.
Latest version from MIPLib is from 2010 so that's not going to happen (due being obsolete).Do you already have an integer linear programming benchmark? That would be interesting.
MIPLIB http://miplib.zib.de/ contains multiple benchmark instances of linear programming problems.
SCIP http://scip.zib.de/ is a non-commercial solver and running these benchmark instances seems to be quite easy: http://scip.zib.de/doc/html/SHELL.php
Apparently it's single threaded only. But might still be interesting for IPC comparisons.
MIPLIB is only a collection of integer linear programming problem instances. To solve these problem instances a solver like SCIP (non-commerical) or Gurobi (commercial) is required. SCIP seems to be well maintained.Latest version from MIPLib is from 2010 so that's not going to happen (due being obsolete).
That's understandable.It probably would, but that isn't very convinient for benchmarking.
When you have close to 30 different workloads and multiple platforms to test, the time spent to test each workload really adds up.
I think I just found the workload.That's understandable.
The reason why I would have liked to have more CFD-based benchmarks is because they are one of the few workloads that are sensitive to memory latency, and given Ryzen's unique issues with latency, it would have been quite useful if there was a way of including them in your testing. Yes Euler3D does the job but I just wanted a little more sophistication.
So it involves compressibility in Eulerian flows? No problem. Thanks for including it.I think I just found the workload.
Eulerian variable density solver, based on Robert Bridson book.
Pure C++ solution, with no dependencies on external math libraries.
Adding the timing for benchmarking use was easy as well and the performance seems to be very constant.
Still need to try which compiler has the best performance across the different platforms thou.
Based on the code I'd say ICL 2018 will be superior, in which case some patching is required.
Anyway, I'll be adding it regardless if you like it or not
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