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NASA Runs Competition To Help Make Old Fortran Code Faster (bbc.com)
NASA is seeking help from coders to speed up the software it uses to design experimental aircraft. From a report on BBC: It is running a competition that will share $55,000 between the top two people who can make its FUN3D software run up to 10,000 times faster. The FUN3D code is used to model how air flows around simulated aircraft in a supercomputer. The software was developed in the 1980s and is written in an older computer programming language called Fortran. "This is the ultimate 'geek' dream assignment," said Doug Rohn, head of NASA's transformative aeronautics concepts program that makes heavy use of the FUN3D code. In a statement, Mr Rohn said the software is used on the agency's Pleiades supercomputer to test early designs of futuristic aircraft. The software suite tests them using computational fluid dynamics, which make heavy use of complicated mathematical formulae and data structures to see how well the designs work.
1. Run it on better hardware.
2. Re-write the compiler to optimize this code in the best way possible.
3. Re-write the code so it provides optimal input to the compiler.
4. Come up with a new algorithm.
5 and beyond: Left as an exercise to the reader.
Assuming any improvements from #1 and #2 don't "count" for this contest, that leaves you with 3 and 4.
Unless the code is brain-dead there is no way you'll get anywhere close to 10,000 improvement JUST by #3. You MIGHT get it with a combination of #3 and #1 and/or #2 vs. just #1 and #2 alone. That is to say, changes in hardware and compilers may give an opportunity to re-factor the code to get huge improvements vs. un-modified code on new compilers and new hardware.
The big win will be in #4, but only if there are better algorithms out there or someone can come up with one. As with re-factoring the code, changes in hardware and corresponding changes in compilers may turn an algorithm that was inefficient in the 1980s into something that is best-in-class today.
5 and beyond are open-ended and the sky is the limit.
Knowledge is how to play a game, intelligence is how to win, wisdom is knowing what game to play.
They want a 10000 times speed up. They would not ask for such if the capability to do that was just lying on their hardware, idle. They either already have the GPU cores to make the calculations, and those are not in use - or they at least expect the same approach, but to make use of multiple-cores that are similarly idle. Otherwise asking for that kind of improvement is simply idiotic. (I think that for this price it is idiotic anyway, they should proper fund that thing).
-><- no
Jesus tits.
Both of you should google 'Pleiades supercomputer specs'. 100 nodes of 10,000 have GPUs. They are currently at near 100% utilization. The do have enough GPU equipped nodes for someone to prove the speedup and for them to start slapping in GPUs and upgraded power supplies.
Alternatively: Spin off the numeric parts to SSE. Use fixed point math routines.
John McAfee 'It was like that time I hired that Bangkok prostitute; to do my taxes, while I fucked my accountant'
System Architecture
Manufacturer: SGI
161 racks (11,472 nodes)
7.25 Pflop/s peak cluster
5.95 Pflop/s LINPACK rating (#13 on November 2016 TOP500 list)
175 Tflop/s HPCG rating (#9 on November 2016 HPCG list)
Total CPU cores: 246,048
Total memory: 938 TB
2 racks (64 nodes total) enhanced with NVIDIA graphics processing units (GPUs)
184,320 CUDA cores
0.275 Pflop/s total
1 rack (32 nodes total) enhanced with Intel Xeon Phi co-processors (MICs)
3,840 MIC cores
0.064 Pflop/s total
Operating Environment
Operating system: SUSE® Linux®
Job scheduler: Altair PBS Professional®
Compilers: Intel and GNU C, C++ and Fortran
MPI: SGI MPT
Full specs here.
Sounds like stone soup to me. CUDA cores, Phi coprocessors, SGI interconnects, Linux OS because nothing else in the whole wide world could talk to all of that...
Ick. Keep your prize money.
Weaselmancer
rediculous.
Sometimes, years after you finish a job (that you never really liked the solution to) a better solution comes to you.
Also: In the 1980s they didn't have a 10,000 node cluster, Multicore CPUs, SSI, Nvidia, ASICs, FPGAs or Gigabytes of RAM. They barely had math coprocessors and blitters.
If at the end of a job, you don't know how to do a it better, that proves you haven't learned anything since you started.
John McAfee 'It was like that time I hired that Bangkok prostitute; to do my taxes, while I fucked my accountant'