Mahuika's new CPU nodes are in an Early Access Programme (EAP) phase and not fully in production.
Early Access Programme
Prior to launching Mahuika's newest CPU nodes for general production, we are allowing early access to help us identify any issues with:
accessing the new nodes
codes that don’t run or have issues running
comparing performance to the old nodes
If you’d like to participate as tester / early access user for the new Mahuika CPU nodes you are welcome to try them out. If you want access to our temporary testing project to run jobs or benchmarks free of charge, refer to the Temporary Project section below and reach out to NeSI Support.
Before accessing the new nodes, please review these important points. If you have any questions, contact NeSI Support.
- To access the new Milan CPUs for 'free' through the course of this testing phase, you can request to be added to the temporary test project account
nesi03638, with the condition that you only use it for testing and benchmarking these new nodes. See the Benchmarking section below for more details.
- Jobs are submitted from the same Mahuika login node that you currently use, however you will need to explicitly specify the
milanpartition in your
sbatchcommand line. See the Slurm Configuration section below for more details.
- We're currently allowing up to 8 nodes per user, 24 hour maximum walltime. To request more than that, contact NeSI Support.
- We're asking early access users to let us know of any issues, challenges, or suggestions for improving your experience getting onto and using the new nodes. We also welcome any testing that compares your job(s) performance on the new nodes against the older nodes. All feedback and insights should be sent to NeSI Support.
For more details on the new Mahuika Extension technology and what we're requesting in terms of benchmarking, please read the information below.
Differences from original Mahuika compute nodes
Each node has two AMD Milan CPUs, each with 8 "chiplets" of 8 cores and one level 3 cache, so each node has a total of 128 cores or 256 hyperthreaded CPUs. This represents a significant increase of the number CPUs per node compared to the Broadwell nodes (36 cores).
The memory available to Slurm jobs is 460 GB per node, so approximately 1800 MB per CPU.
Only 30 nodes are available so far, but that number will eventually increase to 64, 8 of which will have double the memory.
The existing Mahuika compute nodes use Linux Centos 7.4 while the new ones use Rocky 8.5. These are closely related Linux distributions. The move from 7 to 8 is more significant than the move from Centos to Rocky.
Many system libraries have changed version numbers between versions 7 and 8, so some software compiled on Centos 7 will not run as-is on Rocky 8. This can result in the runtime error
error while loading shared libraries:... cannot open shared object file, which can be fixed by providing a copy of the old system library.
We have repaired several of our existing environment modules that way. For programs which you have compiled yourself, we have installed a new environment module that provides many of the Centos 7 libraries:
module load LegacySystemLibs/7
Please let us know if that isn't sufficient to get your existing compiled code running on the new nodes.
Of course you can also recompile code inside a job run in the milan partition and so produce an executable linked against the new system libraries, but then that would be unlikely to work on the old nodes.
In the longer term all Mahuika nodes will be upgraded to Rocky 8.
Older Intel and Cray software
/opt/cray contain software which was installed on Mahuika when we purchased it rather than installed by the NeSI Application Support team. They are not present on the new nodes. As with the system libraries, you could take a copy of these libraries and carry on, but it is best to migrate away from using them if possible.
This affects our pre-2020 toolchains such as intel/2018b, but we should have newer versions of such software already installed in most cases.
Intel MKL performance
In many ways, Intel's MKL is the best implementation of the BLAS and LAPACK libraries to which we have access, which is why we use it in our "intel" and "gimkl" toolchains. Unfortunately, recent versions of MKL deliberately choose not to use the accelerated AVX instructions when not running on an Intel CPU.
In order to persuade MKL to use the same fast optimised kernels on the new AMD Milan CPUs, you can do
module load AlwaysIntelMKL
We have set that as the default for our most recent toolchain gimkl/2022a.
Two alternative implementations have also been installed: OpenBLAS and BLIS. If you try them then please let us know if they work better than MKL for your application. BLIS is expected to perform well as a BLAS alternative but not match MKL's LAPACK performance.
Do I need to recompile my code?
Except for possible missing shared libraries (see above), you should not need to recompile your code. Please let us know if you encounter any issues not listed above.
AMD provides a compiler based on clang (C/C++) and flang (Fortran) which might perform better on their hardware. We have installed it but not integrated it into a high-level toolchain with MPI and BLAS. If you wish to try it:
module load AOCC
For more information on AOCC compiler suite please, visit AMD Optimizing C/C++ and Fortran Compilers (AOCC)
Access to the new nodes is currently only possible via the Slurm
srun commands. There is no ssh access, not even to the nodes where you have a job running. Programs that launch their remote tasks via ssh (eg: ORCA) are not expected to work. Other arbitrary connections to the new compute nodes such as might be used by debuggers, HTTP based progress monitoring, and non-MPI distributed programs such as Dask or PEST, will generally only work if you use the Infiniband address of the compute node, eg: wmc012.ib.hpcf.nesi.org.nz. Networking configuration is expected to be addressed in the future.
To run on the new Milan nodes, you will need to explicitly specify the
milan partition in your
sbatch command line. Jobs are submitted from the same Mahuika login node that you currently use and share the same file system as other cluster nodes.
sbatch -p milan ...
Alternatively, the same effect can be achieved by placing a pragma into the job description file:
Currently up to 10 nodes per account, 7 days maximum job duration. If you need more then please contact us to discuss your requirements.
We at NeSI would love to know how the new AMD Milan CPUs are performing for your code. In order to compare performance against the older nodes, we expect you to run the same job on both node types and provide us with performance results of both. Note that in order to submit the same job to the old nodes, you only need to remove the partition specification (
-p milan) in the
Timing can be obtained through time command, for example:
time srun <command>
Advanced Slurm options for benchmarking
When running benchmarks (and only then!) we recommend using
sbatch --exclusive=user ...
(with short jobs please) so that you have node(s) to yourself and will not be affected by jobs from other users.
There are reports about lower I/O performance when running jobs on Milan nodes. This issue is being investigated and will be addressed once the partition is fully populated. Please, note that the reduced performance does not affect all input/output operations. Please, contact us if you have concerns regarding this issue.
Don't hesitate to contact us at email@example.com. We are available for Zoom sessions if you need to talk to us about specific details of your testing and benchmarking.