Hi Pieter, Sorry that you're still having issues. I think we'll need some more information before going forward:
1) Could you send us the output of "$CHPL_HOME/util/printchplenv --anonymize" ? It's a script that displays the various CHPL_ environment variables. "--anonymize" strips the output of information you may prefer to keep private (machine info, paths). 2) What C compiler are you using? 3) Are you sure that the programs are being launched correctly? This might seem silly, but it's worth double-checking that the programs are actually running on the same hardware (not necessarily the same node though). I'd also like to clarify what you mean by "multi-locale compiled". Is the difference between the programs just the use of the Block domain map, or do you compile with different environment variables set? -Ben Harshbarger On 10/27/16, 5:19 AM, "Pieter Hijma" <[email protected]> wrote: Hi Ben, Thank you for your fast reply and suggestions! I did some more tests and also included stencil operations. First, the vector addition: vectoradd.chpl -------------- use Time; use Random; use BlockDist; //use VisualDebug; config const n = 1024**3/2; // for multi-locale const ProblemDomain : domain(1) dmapped Block(boundingBox = {0..#n}) = {0..#n}; // for single-locale const ProblemDomain : domain(1) = {0..#n}; type float = real(32); proc addNoDomain(c : [] float, a : [] float, b : [] float) { forall (ci, ai, bi) in zip(c, a, b) { ci = ai + bi; } } proc addZip(c : [ProblemDomain] float, a : [ProblemDomain] float, b : [ProblemDomain] float) { forall (ci, ai, bi) in zip(c, a, b) { ci = ai + bi; } } proc addForall(c : [ProblemDomain] float, a : [ProblemDomain] float, b : [ProblemDomain] float) { //startVdebug("vdata"); forall i in ProblemDomain { c[i] = a[i] + b[i]; } //stopVdebug(); } proc addCollective(c : [ProblemDomain] float, a : [ProblemDomain] float, b : [ProblemDomain] float) { c = a + b; } proc output(t : Timer, n, testName) { t.stop(); writeln(testName, " n: ", n); writeln("Time: ", t.elapsed(), "s"); writeln("GFLOPS: ", n / t.elapsed() / 1e9, ""); writeln(); t.clear(); } proc main() { var c : [ProblemDomain] float; var a : [ProblemDomain] float; var b : [ProblemDomain] float; var t : Timer; fillRandom(a, 0); fillRandom(b, 42); t.start(); addNoDomain(c, a, b); output(t, n, "addNoDomain"); t.start(); addZip(c, a, b); output(t, n, "addZip"); t.start(); addForall(c, a, b); output(t, n, "addForall"); t.start(); addCollective(c, a, b); output(t, n, "addCollective"); } ----- On a single locale I get as output: addNoDomain n: 536870912 Time: 0.27961s GFLOPS: 1.92007 addZip n: 536870912 Time: 0.278657s GFLOPS: 1.92664 addForall n: 536870912 Time: 0.278015s GFLOPS: 1.93109 addCollective n: 536870912 Time: 0.278379s GFLOPS: 1.92856 On multi-locale (-nl 1) I get as output: addNoDomain n: 536870912 Time: 2.16806s GFLOPS: 0.247627 addZip n: 536870912 Time: 2.17024s GFLOPS: 0.247378 addForall n: 536870912 Time: 4.78443s GFLOPS: 0.112212 addCollective n: 536870912 Time: 2.19838s GFLOPS: 0.244212 So, indeed, your suggestion improves it by more than a factor two, but it is still close to a factor 8 slower than single-locale. I also used chplvis and verified that there are no gets and puts when running multi-locale with more than one node. The profiling information is clear, but not very helpful (to me): multi-locale (-nl 1): | 65.3451 | wrapcoforall_fn_chpl5 | vectoradd.chpl:26 | | 4.8777 | wrapon_fn_chpl35 | vectoradd.chpl:26 | single-locale: | 5.0019 | wrapcoforall_fn_chpl5 | vectoradd.chpl:26 | For stencil operations, I used the following program: 1d-convolution.chpl ------------------- use Time; use Random; use StencilDist; config const n = 1024**3/2; const ProblemDomain : domain(1) dmapped Stencil(boundingBox = {0..#n}, fluff = (1,)) = {0..#n}; const InnerDomain : subdomain(ProblemDomain) = {1..n-2}; proc convolveIndices(output : [ProblemDomain] real(32), input : [ProblemDomain] real(32)) { forall i in InnerDomain { output[i] = ((input[i-1] + input[i] + input[i+1])/3:real(32)); } } proc convolveZip(output : [ProblemDomain] real(32), input : [ProblemDomain] real(32)) { forall (im1, i, ip1) in zip(InnerDomain.translate(-1), InnerDomain, InnerDomain.translate(1)) { output[i] = ((input[im1] + input[i] + input[ip1])/3:real(32)); } } proc print(t : Timer, n, s) { t.stop(); writeln(s, ", n: ", n); writeln("Time: ", t.elapsed(), "s"); writeln("GFLOPS: ", 3 * n / 1e9 / t.elapsed()); writeln(); t.clear(); } proc main() { var input : [ProblemDomain] real(32); var output : [ProblemDomain] real(32); var t : Timer; fillRandom(input, 42); t.start(); convolveIndices(output, input); print(t, n, "convolveIndices"); t.start(); convolveZip(output, input); print(t, n, "convolveZip"); } ------ Interestingly, in contrast to your earlier suggestion, the direct indexing works a bit better in this program than the zipped version: Multi-locale (-nl 1): convolveIndices, n: 536870912 Time: 4.27148s GFLOPS: 0.377062 convolveZip, n: 536870912 Time: 4.87291s GFLOPS: 0.330524 Single-locale: convolveIndices, n: 536870912 Time: 0.548804s GFLOPS: 2.93477 convolveZip, n: 536870912 Time: 0.538754s GFLOPS: 2.98951 Again, the multi-locale is about a factor 8 slower than single-locale. By the way, the Stencil distribution is a bit faster than the Block distribution. Thanks in advance for your input, Pieter On 24/10/16 19:20, Ben Harshbarger wrote: > Hi Pieter, > > Thanks for providing the example, that's very helpful. > > Multi-locale performance in Chapel is not yet where we'd like it to be, but we've done a lot of work over the past few releases to get cases like yours performing well. It's surprising that using Block results in that much of a difference, but I think you would see better performance by iterating over the arrays directly: > > ``` > // replace the loop in the 'add' function with this: > forall (ci, ai, bi) in zip(c, a, b) { > ci = ai + bi; > } > ``` > > Block-distributed arrays can leverage the fast-follower optimization to perform better when all arrays being iterated over share the same domain. You can also write that loop in a cleaner way by leveraging array promotion: > > ``` > // This is equivalent to the first loop > c = a + b; > ``` > > However, when I tried the promoted variation on my machine I observed worse performance than the explicit forall-loop. It seems to be related to the way the arguments of the 'add' function are declared. If you replaced "[ProblemDomain] float" with "[] float", performance seems to improve. That surprised a couple of us on the development team, and I'll be looking at that some more today. > > If you're still seeing significantly worse performance with Block compared to the default rectangular domain, and the programs are launched in the same way, that would be odd. You could try profiling using chplvis. I agree though that there shouldn't be any communication in this program. You can find more information on chplvis here in the online 1.14 release documentation: > > http://chapel.cray.com/docs/latest/tools/chplvis/chplvis.html > > I hope that rewriting the loops solves the problem, but let us know if it doesn't and we can continue investigating. > > -Ben Harshbarger > > On 10/24/16, 6:19 AM, "Pieter Hijma" <[email protected]> wrote: > > Dear all, > > My apologies if this has already been asked before. I'm new to the list > and couldn't find it in the archives. > > I experience bad performance when running the multi-locale compiled > version on an InfiniBand equiped cluster > (http://cs.vu.nl/das4/clusters.shtml, VU-site), even with only one node. > Below you find a minimal example that exhibits the same performance > problems as all my programs: > > I compiled chapel-1.14.0 with the following steps: > > export CHPL_TARGET_ARCH=native > make -j > export CHPL_COMM=gasnet > export CHPL_COMM_SUBSTRATE=ibv > make clean > make -j > > I compile the following Chapel code: > > vectoradd.chpl: > --------------- > use Time; > use Random; > use BlockDist; > > config const n = 1024**3; > > // for single-locale > // const ProblemDomain : domain(1) = {0..#n}; > // for multi-locale > const ProblemDomain : domain(1) dmapped Block(boundingBox = {0..#n}) = > {0..#n}; > > type float = real(32); > > proc add(c : [ProblemDomain] float, a : [ProblemDomain] float, > b : [ProblemDomain] float) { > forall i in ProblemDomain { > c[i] = a[i] + b[i]; > } > } > > proc main() { > var c : [ProblemDomain] float; > var a : [ProblemDomain] float; > var b : [ProblemDomain] float; > var t : Timer; > > fillRandom(a, 0); > fillRandom(b, 42); > > t.start(); > add(c, a, b); > t.stop(); > > writeln("n: ", n); > writeln("Time: ", t.elapsed(), "s"); > writeln("GFLOPS: ", n / t.elapsed() / 1e9, "s"); > } > ---- > > I compile this for single-locale with (using no domain maps, see the > comment above in the source): > > chpl -o vectoradd --fast vectoradd.chpl > > I run it with (dual quad core with 2 hardware threads): > > export CHPL_RT_NUM_THREADS_PER_LOCALE=16 > ./vectoradd > > And get as output: > > n: 1073741824 > Time: 0.558806s > GFLOPS: 1.92149s > > However, the performance for multi-locale is much worse: > > I compile this for multi-locale with domain maps, see the comment in the > source): > > CHPL_COMM=gasnet CHPL_COMM_SUBSTRATE=ibv chpl -o vectoradd --fast \ > vectoradd.chpl > > I run it on the same type of node with: > > SSH_SERVERS=`uniq $TMPDIR/machines | tr '\n' ' '` > > export GASNET_PHYSMEM_MAX=1G > export GASNET_IBV_SPAWNER=ssh > export GASNET_SSH_SERVERS="$SSH_SERVERS" > > export CHPL_RT_NUM_THREADS_PER_LOCALE=16 > export CHPL_LAUNCHER=gasnetrun_ibv > export CHPL_COMM=gasnet > export CHPL_COMM_SUBSTRATE=ibv > > ./vectoradd -nl 1 > > And get as output: > > n: 1073741824 > Time: 8.65082s > GFLOPS: 0.12412s > > I would understand a performance difference of say 10% because of > multi-locale execution, but not factors. Is this to be expected from > the current state of Chapel? This performance difference is examplary > for basically all my programs that also are more realistic and use > larger inputs. The performance is strange as there is no communication > necessary (only one node) and the program is using the same amount of > threads. > > Is there any way for me to investigate this using profiling for example? > > By the way, the program does scale well to multiple nodes (which is not > difficult given the baseline): > > 1 | 8.65s > 2 | 2.67s > 4 | 1.69s > 8 | 0.87s > 16 | 0.41s > > Thanks in advance for your input. > > Kind regards, > > Pieter Hijma > > ------------------------------------------------------------------------------ > Check out the vibrant tech community on one of the world's most > engaging tech sites, SlashDot.org! http://sdm.link/slashdot > _______________________________________________ > Chapel-users mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/chapel-users > > ------------------------------------------------------------------------------ The Command Line: Reinvented for Modern Developers Did the resurgence of CLI tooling catch you by surprise? 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