Site-specific Documentation for Public UPC++ Installs

This document provides usage instructions for installations of UPC++ at various computing centers. This document describes command line use of existing UPC++ installations and is not a guide to installing or programming UPC++.

For other types of information:

General information about UPC++ and additional links, see: README.md
Installing the UPC++ software, see: INSTALL.md
Tutorial on programming with UPC++, see: UPC++ Programmer's Guide
Formal details on UPC++ semantics, see: UPC++ Specification

This document is a continuous work-in-progress, the purpose of which is to provide up-to-date information on public installs maintained by (or in collaboration with) the UPC++ team. However, systems are constantly changing. So, please report of any errors or omissions in the issue tracker.

Typically installs of UPC++ are maintained only for the current default versions of the system-provided environment modules such as compilers and CUDA. If you find one of the installs described in this document to be out-of-date with respect to the current defaults, please report using the issue tracker link above.

This document is not a replacement for the documentation provided by the centers, and assumes general familiarity with the use of the systems.

NERSC Cori (Haswell and KNL nodes)

NERSC Cori

Stable installs are available through environment modules. A wrapper is used to transparently dispatch commands such as upcxx to an install appropriate to the currently loaded PrgEnv-{intel,gnu,cray}, craype-{haswell,mic-knl} and compiler (intel, gcc, or cce) environment modules.

Environment Modules

In order to access the UPC++ installation on Cori, is it sufficient to module load upcxx. This environment module is located in the default MODULEPATH.

On Cori, the UPC++ environment modules select a default network of aries. You can optionally specify this explicitly on the compile line with upcxx -network=aries ....

Job launch

The upcxx-run utility provided with UPC++ is a relatively simple wrapper, which in the case of Cori Haswell and KNL nodes uses srun, along with the addition of some sane default core bindings. To have full control over process placement and thread pinning, users are advised to consider launching their UPC++ applications directly with srun. However, one should do so only with the upcxx environment module loaded to ensure the appropriate environment variable settings.

If you would normally have passed -shared-heap to upcxx-run, then you should set the environment variable UPCXX_SHARED_HEAP_SIZE instead. Other relevant environment variables set (or inherited) by upcxx-run can be listed by adding -show to your upcxx-run command. Additional information is available in the Advanced Job Launch chapter of the UPC++ v1.0 Programmer's Guide.

Single-node runs

On a system like Cori, there are multiple complications related to launch of executables compiled for -network=smp such that no use of srun (or simple wrappers around it) can provide a satisfactory solution in general. Therefore, we recommend that for single-node (shared memory) application runs on Cori, one should compile for the default network (aries). It is also acceptable to use -network=mpi, such as may be required for some hybrid applications (UPC++ and MPI in the same executable). However, note that in multi-node runs -network=mpi imposes a significant performance penalty.

Batch jobs

By default, batch jobs on Cori inherit both $PATH and the $MODULEPATH from the environment at the time the job is submitted/requested using sbatch or salloc. So, no additional steps are needed to use upcxx-run if a upcxx environment module was loaded when sbatch or salloc ran.

Interactive example:

cori$ module load upcxx

cori$ module switch craype-haswell craype-mic-knl # both work

cori$ upcxx --version
UPC++ version 2022.3.0  / gex-2022.3.0-0-gd509b6a
Citing UPC++ in publication? Please see: https://upcxx.lbl.gov/publications
Copyright (c) 2022, The Regents of the University of California,
through Lawrence Berkeley National Laboratory.
https://upcxx.lbl.gov

icpc (ICC) 19.0.3.199 20190206
Copyright (C) 1985-2019 Intel Corporation.  All rights reserved.

cori$ upcxx -O hello-world.cpp -o hello-world.x

cori$ salloc -C knl -q interactive --nodes 2
salloc: Granted job allocation 28703076
salloc: Waiting for resource configuration
salloc: Nodes nid0[2350-2351] are ready for job

nid02350$ upcxx-run -n 4 -N 2 ./hello-world.x
Hello world from process 0 out of 4 processes
Hello world from process 2 out of 4 processes
Hello world from process 1 out of 4 processes
Hello world from process 3 out of 4 processes

CMake

A UPCXX CMake package is provided in the UPC++ install on Cori, as described in README.md. Thus with the upcxx environment module loaded, CMake should "just work" on Cori. However, /usr/bin/cmake on Cori is fairly old and users may want to use a newer version via module load cmake.

Running 64-PPN on Haswell Nodes

Running 64 UPC++ processes per node on Cori Haswell nodes (using both hardware threads of all 32 cores) requires a non-default value (4M or larger) for the default size of "hugepages". This can be achieved by loading an appropriate craype-hugepages[size] environment module at run time or by setting the environment variable $HUGETLB_DEFAULT_PAGE_SIZE to a supported value of 4M or larger.

For more information on hugepages, run man intro_hugepages on a Cori login node. However, one should disregard the text describing PGAS models (and $XT_SYMMETRIC_HEAP_SIZE in particular) as these apply to the Cray-provided PGAS implementations, and not to GASNet-based ones such as UPC++.

NERSC Perlmutter

Perlmutter

Stable installs are available through environment modules. A wrapper is used to transparently dispatch commands such as upcxx to an install appropriate to the currently loaded PrgEnv-{gnu,cray,nvidia,aocc} and compiler (gcc, cce, nvidia or aocc) environment modules.

Environment Modules

In order to access the UPC++ installation on Perlmutter, one must run

$ module use /global/common/software/m2878/perlmutter/modulefiles

to add a non-default directory to the MODULEPATH before the UPC++ environment modules will be accessible. We recommend inclusion of this command in ones shell startup files, such as $HOME/.login or $HOME/.bash_profile.

If not adding the command to ones shell startup files, the module use ... command will be required once per login shell in which you need a upcxx environment module.

Environment modules provide two alternative installations of the UPC++ library:

upcxx-cuda
This module supports "memory kinds", a UPC++ feature that enables communication to/from CUDA memory when utilizing upcxx::device_allocator.
upcxx
This omits support for upcxx::device_allocator<upcxx::cuda_device>, resulting in a small potential speed-up for applications which do not require this feature.

On Perlmutter, the UPC++ environment modules select a default network of ofi. You can optionally specify this explicitly on the compile line with upcxx -network=ofi ....

Caveats

Support in UPC++ for the HPE Cray EX platform utilizes GASNet-EX's ofi-conduit which is currently considered "experimental". While support is believed to be complete and correct, performance has not yet been tuned. Every run of a UPC++ application on Perlmutter will issue a warning message to remind you of this.

The installs provided on Perlmutter utilize the Cray Programming Environment, and the cc and CC compiler wrappers in particular. It is possible to use upcxx (or CC and upcxx-meta) to link code compiled with the "native compliers" such as g++ and nvc++ (provided they match the PrgEnv-* module). However, direct use of the native compilers to link UPC++ code is not supported with these installs.

Currently, we have insufficient experience with PrgEnv-nvidia and PrgEnv-aocc to include them in our list of supported compilers. However, we are providing corresponding builds on Perlmutter. We encourage reporting (to our issue tracker) of difficulties specific to these two PrgEnv's.

Job launch

The upcxx-run utility provided with UPC++ is a relatively simple wrapper, which in the case of Perlmutter uses srun. To have full control over process placement, thread pinning and GPU allocation, users are advised to consider launching their UPC++ applications directly with srun. However, one should do so only with the upcxx or upcxx-cuda environment module loaded to ensure the appropriate environment variable settings.

If you would normally have passed -shared-heap to upcxx-run, then you should set the environment variable UPCXX_SHARED_HEAP_SIZE instead. Other relevant environment variables set (or inherited) by upcxx-run can be listed by adding -show to your upcxx-run command. Additional information is available in the Advanced Job Launch chapter of the UPC++ v1.0 Programmer's Guide.

Single-node runs

On a system like Perlmutter, there are multiple complications related to launch of executables compiled for -network=smp such that no use of srun (or simple wrappers around it) can provide a satisfactory solution in general. Therefore, we recommend that for single-node (shared memory) application runs on Perlmutter, one should compile for the default network (ofi). It is also acceptable to use -network=mpi, such as may be required for some hybrid applications (UPC++ and MPI in the same executable). However, note that in multi-node runs -network=mpi imposes a significant performance penalty.

Batch jobs

By default, batch jobs on Perlmutter inherit both $PATH and the $MODULEPATH from the environment at the time the job is submitted/requested using sbatch or salloc. So, no additional steps are needed to use upcxx-run if a upcxx environment module was loaded when sbatch or salloc ran.

Interactive example:

perlmutter$ module use /global/common/software/m2878/perlmutter/modulefiles

perlmutter$ module load upcxx

perlmutter$ upcxx --version
UPC++ version 2022.3.0  / gex-2022.3.0-0-gd509b6a
Citing UPC++ in publication? Please see: https://upcxx.lbl.gov/publications
Copyright (c) 2022, The Regents of the University of California,
through Lawrence Berkeley National Laboratory.
https://upcxx.lbl.gov

nvc++ 21.11-0 64-bit target on x86-64 Linux -tp zen2-64
NVIDIA Compilers and Tools
Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES.  All rights reserved.

perlmutter$ upcxx -O hello-world.cpp -o hello-world.x

perlmutter$ salloc -C gpu -q interactive --nodes 2
salloc: Granted job allocation 1722947
salloc: Waiting for resource configuration
salloc: Nodes nid[002700-002701] are ready for job

nid002700$ upcxx-run -n 4 -N 2 ./hello-world.x
[... an expected WARNING ...]
Hello world from process 0 out of 4 processes
Hello world from process 1 out of 4 processes
Hello world from process 2 out of 4 processes
Hello world from process 3 out of 4 processes

CMake

A UPCXX CMake package is provided in the UPC++ install on Perlmutter, as described in README.md. Thus with the upcxx environment module loaded, CMake should "just work".

OLCF Summit

Stable installs are available through environment modules. A wrapper is used to transparently dispatch commands such as upcxx to an install appropriate to the currently loaded compiler environment module.

Environment Modules

In order to access the UPC++ installation on Summit, one must run

$ module use /gpfs/alpine/world-shared/csc296/summit/modulefiles

to add a non-default directory to the MODULEPATH before the UPC++ environment modules will be accessible. We recommend this be done in ones shell startup files, such as $HOME/.login or $HOME/.bash_profile. However, to ensure compatibility with other OLCF systems sharing the same $HOME, the following form should be used:

$ module use /gpfs/alpine/world-shared/csc296/$LMOD_SYSTEM_NAME/modulefiles

If not adding the command to ones shell startup files, the module use ... command will be required once per login shell in which you need a upcxx environment module.

Environment modules provide two alternative installations of the UPC++ library:

upcxx-cuda
This module supports "memory kinds", a UPC++ feature that enables communication to/from CUDA memory when utilizing upcxx::device_allocator. The default version uses GPUDirect RDMA capabilities of the GPU and NIC on Summit to perform GPU memory transfers at a speed comparable to host memory.
This module supports the gcc and pgi compiler families.
upcxx
This module supports the gcc and pgi compiler families, but lacks support for upcxx::device_allocator<upcxx::cuda_device>.

On Summit, the UPC++ environment modules select a default network of ibv. You can optionally specify this explicitly on the compile line with upcxx -network=ibv ....

Caveats

No support for IBM XL compilers

Please note that UPC++ does not yet work with the IBM XL compilers (the default compiler family on Summit).

Module name conflicts with E4S SDK

Currently the default MODULEPATH on Summit includes center-provided E4S SDK installs of UPC++ which are not (yet) as well integrated as the ones described here. It is currently safe to load upcxx and upcxx-cuda if one wishes to use the latest installs described here (the default, and our strong recommendation). However, module load upcxx/[version] may resolve to something different than what one was expecting.

The MODULEPATH may change each time one loads a gcc module, among others. This could silently give the E4S SDK installs precedence over the ones intended by the module use command above. Consequently, it is advisable to check prior to loading a upcxx environment module, as follows. A command such as module --loc show upcxx/2022.3.0 will show the full path which would be loaded (without making changes to ones environment). If the result does not begin with /gpfs/alpine/world-shared/csc296, then one should repeat the module use command above to restore the precedence of the installs provided by the maintainers of UPC++.

Note that these changes to MODULEPATH are only relevant until you have loaded a UPC++ environment module.

Job launch

The upcxx-run utility provided with UPC++ is a relatively simple wrapper around the jsrun job launcher on Summit. The majority of the resource allocation/placement capabilities of jsrun have no equivalent in upcxx-run. So due to the complexity of a Summit compute node, we strongly discourage use of upcxx-run for all but the simplest cases. This is especially important when using GPUs, since it is impractical to coerce upcxx-run to pass the appropriate arguments to jsrun on your behalf.

Instead of using upcxx-run or jsrun for job launch on Summit, we recommend use of the upcxx-jsrun script we have provided. This script wraps jsrun to set certain environment variables appropriate to running UPC++ applications, and to accept additional (non-jsrun) options which are specific to UPC++ or which automate otherwise error-prone settings. Other than --help, which upcxx-jsrun acts on alone, all jsrun options are available via upcxx-jsrun with some caveats noted in the paragraphs which follow.

Here are some of the most commonly used upcxx-jsrun command-line options.
Run upcxx-jsrun --help for a more complete list.

--shared-heap VAL
Behaves just as with upcxx-run
--1-hca
Binds each process to one HCA (default)
--2-hca
Binds each process to two HCAs
--4-hca
Binds each process to all four HCAs
--high-bandwidth
Binds processes to the network interfaces appropriate for highest bandwidth
--low-latency
Binds processes to the network interfaces appropriate for lowest latency
--by-gpu[=N]
Create/bind processes into Resource Set by GPU Creates N processes (default 7), bound to 7 cores of one socket, with 1 GPU
--by-socket[=N]
Create/bind processes into Resource Set by socket Creates N processes (default 21), bound to one socket, with 3 GPUs

The section Network ports on Summit provides a description of the four HCAs on a Summit node, and how they are connected to the two sockets. The "hca" and "latency/bandwidth" options are provided to simplify the process of selecting a good binding of processes to HCAs. This is probably the most important role of upcxx-jsrun, because there are no equivalent jsrun options.

With --1-hca (the default), each process will be bound to a single HCA which is near to the process.

When --2-hca is passed, each process will be bound to two HCAs. The --high-bandwidth and --low-latency options determine which pairs of HCAs are selected. Between these two option, the high-bandwidth option is the default because it corresponds to the most common case in which use of two HCAs per process is preferred over one (as will be described below).

When --4-hca is passed, each process is bound to all four HCAs. This option is included only for completeness and generally provides worse performance than the alternatives.

The default of --1-hca has been selected because our experience has found the use of a single HCA per process to provide the best latency and bandwidth for a wide class of applications. The only notable exception is applications which desire to saturate both network rails from a single socket at a time, such as due to communication in "bursts" or use of only one socket (or process) per node. In such a case, we recommend passing --2-hca (with the default --high-bandwidth) in order to enable each process to use both I/O buses and network rails. However, this can increase latency and reduce the peak aggregate bandwidth of both sockets communicating simultaneously.

Of course, "your mileage may vary" and you are encouraged to try non-default options to determine which provide the best performance for your application.

For many combinations of the options above, there are multiple equivalent bindings available (such as two HCAs near to each socket in the --1-hca case). When multiple equivalent bindings exist, processes will be assigned to them round-robin.

In addition to the options described above for HCA binding, there are --by-gpu and --by-socket options to simplify construction of two of the more common cases of resource sets. Use of either is entirely optional, but in their absence be aware that jsrun defaults to a single CPU core per resource set. If you do choose to use them, be aware that they are mutually exclusive and that they are implemented using the following jsrun options: --rs_per_host, --cpu_per_rs, --gpu_per_rs, --tasks_per_rs, --launch_distribution and -bind. So, use of the --by-* options may interact in undesired ways with explicit use of those options and with any options documented as conflicting with them.

To become familiar with use of jsrun on Summit, you should read the Summit User Guide. Other than --help, which upcxx-jsrun acts on alone, all jsrun options are available via upcxx-jsrun with the caveats noted above.

Advanced use of upcxx-jsrun

If you need to use upcxx-run options not accepted by upcxx-jsrun, then it may be necessary to set environment variables to mimic those options. To do so, follow the instructions on launch of UPC++ applications using a system-provided "native" spawner, in the section Advanced Job Launch in the UPC++ Programmer's Guide.

If you need to understand the operation of upcxx-jsrun, the --show and --show-full options may be of use. Passing either of these options will echo (a portion of) a jsrun command rather than executing it. The use of --show will print the jsrun command and its options, eliding the UPC++ executable and its arguments. This is sufficient to understand the operation of the --by-* options.

The --*-hca and --shared-heap options are implemented in two steps where the second is accomplished by specifying upcxx-jsrun as the process which jsrun should launch. The "front end" instance of upcxx-jsrun passes arguments to the multiple "back end" instances of upcxx-jsrun using environment variables. Use of --show-full adds the relevant environment settings to the --show output. However, be advised that there is no guarantee this environment-based internal interface will remain fixed.

If you wish to determine the actual core bindings and GASNET_IBV_PORTS assigned to each process for a given set of [options] one can run the following:

upcxx-jsrun --stdio_mode prepended [options] \
  -- sh -c 'echo HCAs=$GASNET_IBV_PORTS host=$(hostname) cores=$(hwloc-calc --whole-system -I core $(hwloc-bind --get))' | sort -V

with output looking something like the following for --2-hca --by-gpu=1 in a two node allocation:

1: 0: HCAs=mlx5_0+mlx5_3 host=d04n12 cores=0,1,2,3,4,5,6
1: 1: HCAs=mlx5_1+mlx5_2 host=d04n12 cores=7,8,9,10,11,12,13
1: 2: HCAs=mlx5_0+mlx5_3 host=d04n12 cores=14,15,16,17,18,19,20
1: 3: HCAs=mlx5_1+mlx5_2 host=d04n12 cores=22,23,24,25,26,27,28
1: 4: HCAs=mlx5_0+mlx5_3 host=d04n12 cores=29,30,31,32,33,34,35
1: 5: HCAs=mlx5_1+mlx5_2 host=d04n12 cores=36,37,38,39,40,41,42
1: 6: HCAs=mlx5_0+mlx5_3 host=h35n08 cores=0,1,2,3,4,5,6
1: 7: HCAs=mlx5_1+mlx5_2 host=h35n08 cores=7,8,9,10,11,12,13
1: 8: HCAs=mlx5_0+mlx5_3 host=h35n08 cores=14,15,16,17,18,19,20
1: 9: HCAs=mlx5_1+mlx5_2 host=h35n08 cores=22,23,24,25,26,27,28
1: 10: HCAs=mlx5_0+mlx5_3 host=h35n08 cores=29,30,31,32,33,34,35
1: 11: HCAs=mlx5_1+mlx5_2 host=h35n08 cores=36,37,38,39,40,41,42

Where the 1: indicates this is the first jsrun in a given job, and the second field is a rank (both due to use of --stdio_mode prepended). Cores 21 and 43 are reserved to system use and thus never appear this output.

Single-node runs

On a system configured as Summit has been, there are multiple complications related to launch of executables compiled for -network=smp such that no use of jsrun (or simple wrappers around it) can provide a satisfactory solution in general. Therefore, the provided installations on Summit do not support -network=smp. We recommend that for single-node (shared memory) application runs on Summit, one should compile for the default network (ibv). It is also acceptable to use -network=mpi, such as may be required for some hybrid applications (UPC++ and MPI in the same executable). However, note that in multi-node runs -network=mpi imposes a significant performance penalty.

Batch jobs

By default, batch jobs on Summit inherit both $PATH and the $MODULEPATH from the environment at the time the job is submitted using bsub. So, no additional steps are needed in batch jobs using upcxx-jsrun if a upcxx or upcxx-cuda environment module was loaded when the job was submitted.

Interactive example (assuming module use in shell startup files)

summit$ module load gcc   # since default `xl` is not supported

summit$ module load upcxx-cuda

summit$ upcxx -V
UPC++ version 2022.3.0  / gex-2022.3.0-0-gd509b6a
Citing UPC++ in publication? Please see: https://upcxx.lbl.gov/publications
Copyright (c) 2022, The Regents of the University of California,
through Lawrence Berkeley National Laboratory.
https://upcxx.lbl.gov

g++ (GCC) 9.1.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

summit$ upcxx -O hello-world.cpp -o hello-world.x

summit$ bsub -W 5 -nnodes 2 -P [project] -Is bash
Job <714297> is submitted to default queue <batch>.
<<Waiting for dispatch ...>>
<<Starting on batch2>>

bash-4.2$ upcxx-jsrun --by-socket=1 ./hello-world.x
Hello world from process 0 out of 4 processes
Hello world from process 2 out of 4 processes
Hello world from process 3 out of 4 processes
Hello world from process 1 out of 4 processes

CMake

A UPCXX CMake package is provided in the UPC++ install on Summit, as described in README.md. CMake is available on Summit via module load cmake. With the upcxx and cmake environment modules both loaded, CMake will additionally require either CXX=mpicxx in the environment or -DCMAKE_CXX_COMPILER=mpicxx on the command line.

Support for GPUDirect RDMA

The default version of the upcxx-cuda environment module (but not the upcxx one) includes support for the GPUDirect RDMA (GDR) capabilities of the GPUs and InfiniBand hardware on Summit. This enables communication to and from GPU memory without use of intermediate buffers in host memory. This delivers significantly faster GPU memory transfers via upcxx::copy() than previous releases without GDR support. However, there are currently some outstanding known issues.

The upcxx-cuda environment module will initialize your environment with settings intended to provide correctness by default, compensating for the known issues in GDR support. This is true even where this may come at the expense of performance. At this time we strongly advise against changing any GASNET_* or UPCXX_* environment variables set by the upcxx-cuda environment module unless you are certain you know what you are doing. (Running module show upcxx-cuda will show what it sets).

Network ports on Summit

Each Summit compute node has two CPU sockets, each with its own I/O bus. Each I/O bus has a connection to the single InfiniBand Host Channel Adapter (HCA). The HCA is connected to two "rails" (network ports). This combination of two I/O buses and two network rails results in four distinct paths between memory and network. The software stack exposes these paths as four (logical) HCAs named mlx5_0 through mlx5_3.

HCA	I/O bus	rail
mlx5_0	Socket 0	A
mlx5_1	Socket 0	B
mlx5_2	Socket 1	A
mlx5_3	Socket 1	B

Which HCAs are used in a UPC++ application is determined at run time by the GASNET_IBV_PORTS family of environment variables. Which ports are used can have a measurable impact on network performance, but unfortunately there is no "one size fits all" optimal setting. For instance, the lowest latency is obtained by having each process use only one HCAs on the I/O bus of the socket where it is executing. Meanwhile, obtaining the maximum bandwidth of a given network rail from a single socket requires use of both I/O buses.

More information can be found in slides which describe the node layout from the point of view of running MPI applications on Summit. However, the manner in which MPI and UPC++ use multiple HCAs differs, which accounts for small differences between those recommendations and the settings used by upcxx-jsrun and described below.

Use of the appropriate options to the upcxx-jsrun script will automate setting of the GASNET_IBV_PORTS family of environment variables to use the recommended HCA(s). However, the following recommendations may be used if for some reason one cannot use the upcxx-jsrun script.

Similar to the MPI environment variables described in those slides, a _1 suffix on GASNET_IBV_PORTS specifies the value to be used for processes bound to socket 1. While one can set GASNET_IBV_PORTS_0 for processes bound to socket 0, below we will instead use the un-suffixed variable GASNET_IBV_PORTS because it specifies a default to be used not only for socket 0 (due to the absence of a GASNET_IBV_PORTS_0 setting), but for unbound processes as well.

Processes each bound to a single socket -- latency-sensitive.
To get the best latency from both sockets requires use only one HCA, attached to the I/O bus nearest to the socket.
- GASNET_IBV_PORTS=mlx5_0
- GASNET_IBV_PORTS_1=mlx5_3
Processes each bound to a single socket -- bandwidth-sensitive.
How to get the full bandwidth from both sockets depends on the communication behaviors of the application. If both sockets are communicating at the same time, then the latency-optimized settings immediately above are typically sufficient to achieve peak aggregate bandwidth. However, if a single communicating socket (at a given time) is to achieve the peak bandwidth a different pair of process-specific settings is required (which comes at the cost of slightly increased mean latency).
- GASNET_IBV_PORTS=mlx5_0+mlx5_3
- GASNET_IBV_PORTS_1=mlx5_1+mlx5_2
Processes each bound to a single socket -- mixed or unknown behavior.
In general, the use of a single HCA is the best option in terms of the minimum latency and peak aggregate (per-node) bandwidth. For this reason the latency-optimizing settings (presented first) are the nearest thing to a "generic" application recommendation.
Processes unbound or individually spanning both sockets.
In this case is it difficult to make a good recommendation since any given HCA has a 50/50 chance of being distant from the socket on which a given process is executing. The best average performance comes from "splitting the pain" using two of the available paths per process with one near to each socket, and together spanning both network rails. This leads to the same settings (presented second) as recommended for achieving peak bandwidth from a single socket at a time.

Correctness with multiple HCAs

The use of multiple HCAs per node will typically open the possibility of a corner-case correctness problem, for which the recommended work-around is to set GASNET_USE_FENCED_PUTS=1 in ones environment. This is done by default in the upcxx and upcxx-cuda environment modules. However, if you launch UPC++ applications without the module loaded, we recommend setting this yourself at run time.

The issue is that, by default, the use of multiple network paths may permit an rput which has signaled operation completion to be overtaken by a subsequently issued rput, rget or rpc. When an rput is overtaken by another rput to the same location, the earlier value may be stored rather than the latter. When an rget overtakes an rput targeting the same location, it may fail to observe the value stored by the rput. When an rpc overtakes an rput, CPU accesses to the location targeted by the rput is subject to both of the preceding problems. Setting GASNET_USE_FENCED_PUTS=1 prevents this overtaking behavior, in exchange for a penalty in both latency and bandwidth. However, the bandwidth penalty is tiny when compared to the increase due to using multiple HCAs to access both network rails and/or I/O buses.

If you believe your application is free of the X-after-rput patterns described above, you may consider setting GASNET_USE_FENCED_PUTS=0 in your environment at run time. However, when choosing to do so one should be prepared to detect the invalid results which may result if such patterns do occur.

For more details, search for GASNET_USE_FENCED_PUTS in the ibv-conduit README

OLCF Crusher

Stable installs are available through environment modules. A wrapper is used to transparently dispatch commands such as upcxx to an install appropriate to the currently loaded PrgEnv-{gnu,cray,amd} and compiler (gcc, cce, amd) environment modules.

Environment Modules

In order to access the UPC++ installation on Crusher, one must run

$ module use /gpfs/alpine/world-shared/csc296/crusher/modulefiles

to add a non-default directory to the MODULEPATH before the UPC++ environment modules will be accessible. We recommend this be done in ones shell startup files, such as $HOME/.login or $HOME/.bash_profile. However, to ensure compatibility with other OLCF systems sharing the same $HOME, the following form should be used:

$ module use /gpfs/alpine/world-shared/csc296/$LMOD_SYSTEM_NAME/modulefiles

If not adding the command to ones shell startup files, the module use ... command will be required once per login shell in which you need a upcxx environment module.

Environment modules provide two alternative installations of the UPC++ library:

upcxx-hip
This module supports "memory kinds", a UPC++ feature that enables communication to/from CUDA memory when utilizing upcxx::device_allocator.
upcxx
This omits support for upcxx::device_allocator<upcxx::hip>, resulting in a small potential speed-up for applications which do not require this feature.

On Crusher, the UPC++ environment modules select a default network of ofi. You can optionally specify this explicitly on the compile line with upcxx -network=ofi ....

Caveats

Support in UPC++ for the HPE Cray EX platform utilizes GASNet-EX's ofi-conduit which is currently considered "experimental". While support is believed to be complete and correct, performance has not yet been tuned. Every run of a UPC++ application on Crusher will issue a warning message to remind you of this.

The installs provided on Crusher utilize the Cray Programming Environment, and the cc and CC compiler wrappers in particular. It is possible to use upcxx (or CC and upcxx-meta) to link code compiled with the "native compliers" such as g++ and amdclang++ (provided they match the PrgEnv-* module). However, direct use of the native compilers to link UPC++ code is not supported with these installs.

Currently, we have insufficient experience with PrgEnv-amd to include it in our list of supported compilers. However, we are providing corresponding builds on Crusher. We encourage reporting (to our issue tracker) of difficulties specific to this PrgEnv.

Job launch

The upcxx-run utility provided with UPC++ is a relatively simple wrapper, which in the case of Crusher uses srun. To have full control over process placement, thread pinning and GPU allocation, users are advised to consider launching their UPC++ applications directly with srun. However, one should do so only with the upcxx or upcxx-hip environment module loaded to ensure the appropriate environment variable settings.

If you would normally have passed -shared-heap to upcxx-run, then you should set the environment variable UPCXX_SHARED_HEAP_SIZE instead. Other relevant environment variables set (or inherited) by upcxx-run can be listed by adding -show to your upcxx-run command. Additional information is available in the Advanced Job Launch chapter of the UPC++ v1.0 Programmer's Guide.

Single-node runs

On a system like Crusher, there are multiple complications related to launch of executables compiled for -network=smp such that no use of srun (or simple wrappers around it) can provide a satisfactory solution in general. Therefore, we recommend that for single-node (shared memory) application runs on Crusher, one should compile for the default network (ofi). It is also acceptable to use -network=mpi, such as may be required for some hybrid applications (UPC++ and MPI in the same executable). However, note that in multi-node runs -network=mpi imposes a significant performance penalty.

Batch jobs

By default, batch jobs on Crusher inherit both $PATH and the $MODULEPATH from the environment at the time the job is submitted/requested using sbatch or salloc. So, no additional steps are needed to use upcxx-run if a upcxx environment module was loaded when sbatch or salloc ran.

Interactive example:

crusher$ module use /gpfs/alpine/world-shared/csc296/crusher/modulefiles
crusher$ module load upcxx

crusher$ upcxx --version
UPC++ version 2022.3.0  / gex-2022.3.0-0-gd509b6a
Citing UPC++ in publication? Please see: https://upcxx.lbl.gov/publications
Copyright (c) 2022, The Regents of the University of California,
through Lawrence Berkeley National Laboratory.
https://upcxx.lbl.gov

Cray clang version 13.0.0  (24b043d62639ddb4320c86db0b131600fdbc6ec6)
Target: x86_64-unknown-linux-gnu
Thread model: posix
InstalledDir: /opt/cray/pe/cce/13.0.0/cce-clang/x86_64/share/../bin

crusher$ upcxx -O hello-world.cpp -o hello-world.x

crusher$ salloc -t 5 --nodes 2
salloc: Granted job allocation 96088
salloc: Waiting for resource configuration
salloc: Nodes crusher[083-084] are ready for job
crusher083$ upcxx-run -n 4 -N 2 ./hello-world.x
 WARNING: ofi-conduit is experimental and should not be used for
          performance measurements.
          Please see `ofi-conduit/README` for more details.
Hello from 0 of 4
Hello from 1 of 4
Hello from 2 of 4
Hello from 3 of 4

CMake

A UPCXX CMake package is provided in the UPC++ install on Crusher, as described in README.md. Thus with the upcxx environment module loaded, CMake should "just work".

OLCF Spock

Spock at OLCF is very similar to Crusher, but with some differences in hardware and software versions. Consequently, the upcxx environment modules for Spock differ from those for Crusher, and object files, libraries and executables for the two systems are not interchangeable.

Despite those differences, use of upcxx is nearly identical. Everything described immediately above for Crusher is true on Spock, so long as the correct environment modules are used:

$ module use /gpfs/alpine/world-shared/csc296/spock/modulefiles

OR

$ module use /gpfs/alpine/world-shared/csc296/$LMOD_SYSTEM_NAME/modulefiles

ALCF Theta

Stable installs are available through environment modules. A wrapper is used to transparently dispatch commands such as upcxx to an install appropriate to the currently loaded PrgEnv-{intel,gnu,cray} and compiler (intel, gcc, or cce) environment modules.

Environment Modules

In order to access the UPC++ installation on Theta, one must run

$ module use /projects/CSC250STPM17/modulefiles

to add a non-default directory to the MODULEPATH before the UPC++ environment modules will be accessible. We recommend inclusion of this command in ones shell startup files, such as $HOME/.login or $HOME/.bash_profile.

If not adding the command to ones shell startup files, the module use ... command will be required once per login shell and batch job in which you need a upcxx environment module.

It is also possible to instead include the required command in ones $HOME/.modulerc to make it persistent. This file must begin with a #%Module line to be accepted by the module command. This approach may have a slight advantage over the shell startup files in that a module use ... is not needed in a batch job (though module load upcxx still is).
A complete .modulerc suitable for Theta:

#%Module
module use /projects/CSC250STPM17/modulefiles

On Theta, the UPC++ environment modules select a default network of aries. You can optionally specify this explicitly on the compile line with upcxx -network=aries ....

Job launch

The upcxx-run utility provided with UPC++ is a relatively simple wrapper, which in the case of Theta uses aprun. To have full control over process placement and thread pinning, users are advised to consider launching their UPC++ applications directly with aprun. However, one should do so only with the upcxx environment module loaded to ensure the appropriate environment variable settings.

If you would normally have passed -shared-heap to upcxx-run, then you should set the environment variable UPCXX_SHARED_HEAP_SIZE instead. Other relevant environment variables set (or inherited) by upcxx-run can be listed by adding -show to your upcxx-run command. Additional information is available in the Advanced Job Launch chapter of the UPC++ v1.0 Programmer's Guide.

Single-node runs

On a system like Theta, there are multiple complications related to launch of executables compiled for -network=smp such that no use of aprun (or simple wrappers around it) can provide a satisfactory solution in general. Therefore, we recommend that for single-node (shared memory) application runs on Theta, one should compile for the default network (aries). It is also acceptable to use -network=mpi, such as may be required for some hybrid applications (UPC++ and MPI in the same executable). However, note that in multi-node runs -network=mpi imposes a significant performance penalty.

Batch jobs

COBALT jobs (both batch and interactive) do not inherit the necessary settings from the submit-time environment, meaning both the module use ... and module load upcxx may be required in batch jobs which use upcxx-run. This is shown in the example below.

Interactive example

theta$ module use /projects/CSC250STPM17/modulefiles
theta$ module load upcxx

theta$ upcxx --version
UPC++ version 2022.3.0  / gex-2022.3.0-0-gd509b6a
Citing UPC++ in publication? Please see: https://upcxx.lbl.gov/publications
Copyright (c) 2022, The Regents of the University of California,
through Lawrence Berkeley National Laboratory.
https://upcxx.lbl.gov

icpc (ICC) 19.1.0.166 20191121
Copyright (C) 1985-2019 Intel Corporation.  All rights reserved.

theta$ upcxx -O hello-world.cpp -o hello-world.x

theta$ qsub -q debug-cache-quad -t 10 -n 2 -A CSC250STPM17 -I
Connecting to thetamom3 for interactive qsub...
Job routed to queue "debug-cache-quad".
Memory mode set to cache quad for queue debug-cache-quad
Wait for job 418194 to start...
Opening interactive session to 3833,3836
thetamom3$ # Note that modules have reset to defaults
thetamom3$ module use /projects/CSC250STPM17/modulefiles
thetamom3$ module load upcxx
thetamom3$ upcxx-run -n 4 -N 2 ./a.out
Hello from 0 of 4
Hello from 1 of 4
Hello from 3 of 4
Hello from 2 of 4

CMake

A UPCXX CMake package is provided in the UPC++ install on Theta, as described in README.md. While /usr/bin/cmake is too old, sufficiently new CMake versions are available on Theta via module load cmake. With the upcxx and cmake environment modules both loaded, CMake should "just work" on Theta.

NERSC Cori GPU nodes

NERSC Cori GPU

In addition to their primary Cray XC system, Cori, NERSC maintains a small non-production cluster of GPU-equipped nodes connected by multirail InfiniBand. While they share the same home directories and login nodes as the Cray XC system, the GPU nodes are not binary compatible with the XC nodes. The following assumes you have been granted access to the GPU nodes, and that you have read and understand the online documentation for their use.

Though covered in the online documentation, it is worth repeating here that by default allocations of Cori GPU nodes are shared -- you will be running on a system with multiple users and therefore must not trust performance numbers unless you explicitly request an exclusive node allocation.

Stable installs are available through the upcxx-gpu environment modules. A wrapper is used to transparently dispatch commands such as upcxx to an install appropriate to the currently loaded compiler modules. Since these installs do not use Cray's cc and CC wrappers, a loaded intel or gcc environment module will determine which compiler family is used. Note there is no support for cray, pgi, or nvhpc compiler families on the GPU nodes.

Due to differences in the environments (installed networking libraries in particular) one can only load the upcxx-gpu environment module on a cgpu node, not on a Cori login node. This means that compilation of UPC++ applications to be run on the Cori GPU nodes cannot be done on a login node as one would for the Cray XC nodes. Loading the cgpu and cuda environment modules, and a compiler environment module, are all prerequisites for loading the upcxx-gpu environment module.

Since the upcxx-gpu environment module can only be run on the cgpu nodes, compilation is typically done in an interactive session launched using salloc. Since the slurm configuration does change occasionally, one should consult NERSC's online documentation for the proper command, and especially for the options related to allocation of GPUs.

The upcxx-gpu environment module selects a default network of ibv. You can optionally specify this explicitly on the compile line with upcxx -network=ibv ....

Job launch

The upcxx-run utility provided with UPC++ is a relatively simple wrapper, which in the case of the Cori GPU nodes simply runs srun. To have full control over process placement, thread pinning and GPU allocation, users are advised to consider launching their UPC++ applications directly with srun. However, one should do so only with the upcxx-gpu environment module loaded due to the importance of the environment variable settings for use of multiple InfiniBand ports, alluded to above.

If you would normally have passed -shared-heap to upcxx-run, then you should set the environment variable UPCXX_SHARED_HEAP_SIZE instead. Other relevant environment variables set (or inherited) by upcxx-run can be listed by adding -show to your upcxx-run command. Additional information is available in the Advanced Job Launch chapter of the UPC++ v1.0 Programmer's Guide.

Single-node runs

On a system like Cori GPU, there are multiple complications related to launch of executables compiled for -network=smp such that no use of srun (or simple wrappers around it) can provide a satisfactory solution in general. Therefore, we recommend that for single-node (shared memory) application runs on Cori GPU, one should compile for the default network (ibv). It is also acceptable to use -network=mpi, such as may be required for some hybrid applications (UPC++ and MPI in the same executable). However, note that in multi-node runs -network=mpi imposes a significant performance penalty.

Interactive example:

Please note that, contrary to all prior examples, the upcxx (compile) takes place inside the interactive session on the compute nodes.

cori$ module purge
cori$ module load cgpu

cori$ salloc -N2 -C gpu -p gpu --gpus-per-node=1 -t 10
salloc: Pending job allocation 1149547
salloc: job 1149547 queued and waiting for resources
salloc: job 1149547 has been allocated resources
salloc: Granted job allocation 1149547
salloc: Waiting for resource configuration
salloc: Nodes cgpu[02,13] are ready for job

cgpu02$ module load cuda

cgpu02$ module load intel

cgpu02$ module load upcxx-gpu

cgpu02$ upcxx --version
UPC++ version 2022.3.0  / gex-2022.3.0-0-gd509b6a
Citing UPC++ in publication? Please see: https://upcxx.lbl.gov/publications
Copyright (c) 2022, The Regents of the University of California,
through Lawrence Berkeley National Laboratory.
https://upcxx.lbl.gov

icpc (ICC) 19.0.3.199 20190206
Copyright (C) 1985-2019 Intel Corporation.  All rights reserved.

cgpu02$ upcxx -O hello-world.cpp -o hello-world.x

cgpu02$ upcxx-run -n 4 -N 2 ./hello-world.x
Hello world from process 0 out of 4 processes
Hello world from process 2 out of 4 processes
Hello world from process 1 out of 4 processes
Hello world from process 3 out of 4 processes

CMake

A UPCXX CMake package is provided in the UPC++ install on the Cori GPU nodes as described in README.md. Thus with the upcxx-gpu environment module loaded, CMake should "just work". However, /usr/bin/cmake is fairly old and users may want to use a newer version via module load cmake.

Multirail networking on Cori GPU Nodes

Each Cori GPU node has five Mellanox InfiniBand Host Channel Adapters (HCAs) providing a total of nine network ports. Of those, as many as seven are potentially usable for UPC++. The upcxx-gpu environment module will initialize your environment with settings which emphasize correctness over network performance. At this time we strongly advise against changing any GASNET_* or UPCXX_* environment variables set by the upcxx-gpu environment module unless you are certain you know what you are doing. (Running module show upcxx-gpu on a GPU node will show what it sets).

Support for GPUDirect RDMA

The default upcxx-gpu environment module includes support for the GPUDirect RDMA (GDR) capabilities of the GPUs and InfiniBand hardware on the Cori GPU nodes. This enables communication to and from GPU memory without use of intermediate buffers in host memory. This delivers significantly faster GPU memory transfers via upcxx::copy() than previous releases without GDR support. However, there are currently some outstanding known issues.

The upcxx-gpu environment module will initialize your environment with settings intended to provide correctness by default, compensating for the known issues in GDR support. This is true even where this may come at the expense of performance. At this time we strongly advise against changing any GASNET_* or UPCXX_* environment variables set by the upcxx-gpu environment module unless you are certain you know what you are doing. (Running module show upcxx-gpu on a GPU node will show what it sets).

Site-specific Documentation for Public UPC++ Installs

Table of contents

NERSC Cori (Haswell and KNL nodes)

Environment Modules

Job launch

Single-node runs

Batch jobs

Interactive example:

CMake

Running 64-PPN on Haswell Nodes

NERSC Perlmutter

Environment Modules

Caveats

Job launch

Single-node runs

Batch jobs

Interactive example:

CMake

OLCF Summit

Environment Modules

Caveats

No support for IBM XL compilers

Module name conflicts with E4S SDK

Job launch

Advanced use of upcxx-jsrun

Single-node runs

Batch jobs

Interactive example (assuming module use in shell startup files)

CMake

Support for GPUDirect RDMA

Network ports on Summit

Correctness with multiple HCAs

OLCF Crusher

Environment Modules

Caveats

Job launch

Single-node runs

Batch jobs

Interactive example:

CMake

OLCF Spock

ALCF Theta

Environment Modules

Job launch

Single-node runs

Batch jobs

Interactive example

CMake

NERSC Cori GPU nodes

Job launch

Single-node runs

Interactive example:

CMake

Multirail networking on Cori GPU Nodes

Support for GPUDirect RDMA