EESSI Meets Slingshot-11-part2

docs/blog/posts/2026/05/eessi-cray-slingshot11-part2.md

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+---
+author: [Richard]
+date: 2026-05-11 
+slug: EESSI-on-Cray-Slingshot-part2
+---
+
+# MPI at Warp Speed: EESSI Meets Slingshot-11<sub><sup>(part2)</sup></sub>
+
+Building on our initial HPE/Cray Slingshot‑11 results, we further refined MPI tuning and validated the setup using EESSI/2025.06. The outcome is a significant performance improvement, bringing EESSI MPI behavior much closer to vendor tuned Cray MPI environments.
+In our previous blog post, [MPI at Warp Speed: EESSI Meets Slingshot‑11](https://www.eessi.io/docs/blog/2025/11/14/EESSI-on-Cray-Slingshot/), we demonstrated that EESSI could successfully leverage the HPE Cray Slingshot‑11 interconnect via the [host_injections](https://www.eessi.io/docs/site_specific_config/host_injections/) mechanism. Even as a proof‑of‑concept, the results were promising especially for GPU aware MPI communication on NVIDIA Grace Hopper systems.
+We have continued to tune and refine MPI communication while using EESSI/2025.06 software stack. Through updates to several core components and improvements to library configuration, we significantly reduced latency overheads and improved bandwidth utilization across Slingshot‑11.
+In this follow up blog post, we present the results using OSU-Micro-Benchmarks/7.5 and show how close EESSI can now get to native, vendor‑optimized MPI performance on Slingshot‑11 systems. 
+
+### System Architecture
+
+Our target system is [Olivia](https://documentation.sigma2.no/hpc_machines/olivia.html#olivia) which is based on HPE Cray EX platforms for compute and accelerator nodes, and HPE Cray ClusterStor for global storage, all
+connected via HPE Slingshot high-speed interconnect.
+It consists of two main distinct partitions:
+
+- **Partition 1**: x86_64 AMD CPUs without accelerators
+- **Partition 2**: NVIDIA Grace CPUs with Hopper accelerators
+
+### Testing
+
+The following tests were conducted on Olivia accel partition (Grace nodes with Hopper GPUs), using two-node, two-GPU configuration with one MPI task per node. 
+
+We evaluated two OSU Micro-Benchmark builds:
+
+1- OSU-Micro-Benchmarks/7.5-gompi-2024a-CUDA-12.6.0 from EESSI
+
+2- OSU-Micro-Benchmarks/7.5 compiled with PrgEnv-cray.
+
+The following commands were used to run the benchmarks:
+
+`srun -N 2 --ntasks-per-node=1 osu_bibw -i 10 D D`
+
+`srun -N 2 --ntasks-per-node=1 osu_latency -i 10 D D`
+
+![OSU CUDA Bi-bandwidth](OSU‑7.5-CUDA-bibw.png)  ![OSU CUDA Latency](OSU‑7.5-CUDA-Latency.png) 
+
+<details>
+<summary>See details</summary>
+
+<b>Test using OSU-Micro-Benchmarks/7.5-gompi-2024a-CUDA-12.6.0 from EESSI</b>:
+```
+Environment set up to use EESSI (2025.06), have fun!
+
+hostname:
+gpu-1-111
+gpu-1-102
+
+CPU info:
+Vendor ID:                            ARM
+
+Currently Loaded Modules:
+  1) EESSI/2025.06                           12) PMIx/5.0.2-GCCcore-13.3.0
+  2) GCCcore/13.3.0                          13) PRRTE/3.0.5-GCCcore-13.3.0
+  3) GCC/13.3.0                              14) UCC/1.3.0-GCCcore-13.3.0
+  4) numactl/2.0.18-GCCcore-13.3.0           15) OpenMPI/5.0.3-GCC-13.3.0
+  5) libxml2/2.12.7-GCCcore-13.3.0           16) gompi/2024a
+  6) libpciaccess/0.18.1-GCCcore-13.3.0      17) GDRCopy/2.4.1-GCCcore-13.3.0
+  7) hwloc/2.10.0-GCCcore-13.3.0             18) UCX-CUDA/1.16.0-GCCcore-13.3.0-CUDA-12.6.0       (g)
+  8) OpenSSL/3                               19) NCCL/2.22.3-GCCcore-13.3.0-CUDA-12.6.0           (g)
+  9) libevent/2.1.12-GCCcore-13.3.0          20) UCC-CUDA/1.3.0-GCCcore-13.3.0-CUDA-12.6.0        (g)
+ 10) UCX/1.16.0-GCCcore-13.3.0               21) OSU-Micro-Benchmarks/7.5-gompi-2024a-CUDA-12.6.0 (g) 
+ 11) libfabric/1.21.0-GCCcore-13.3.0                
+
+  Where:
+   g:  built for GPU
+
+# OSU MPI-CUDA Bi-Directional Bandwidth Test v7.5
+# Datatype: MPI_CHAR.
+# Size      Bandwidth (MB/s)
+1                       2.57
+2                       5.11
+4                      10.22
+8                      20.66
+16                     40.44
+32                     80.95
+64                    165.02
+128                   329.14
+256                   650.10
+512                  1301.93
+1024                 2608.66
+2048                 5189.90
+4096                10332.67
+8192                19474.04
+16384               28342.00
+32768               33507.82
+65536               37659.55
+131072              41730.65
+262144              44740.60
+524288              45448.67
+1048576             45700.68
+2097152             45895.85
+4194304             46035.77
+
+# OSU MPI-CUDA Latency Test v7.5
+# Datatype: MPI_CHAR.
+# Size       Avg Latency(us)
+1                       2.38
+2                       2.34
+4                       2.34
+8                       2.32
+16                      2.34
+32                      2.34
+64                      2.34
+128                     3.16
+256                     3.31
+512                     3.35
+1024                    3.46
+2048                    3.60
+4096                    3.80
+8192                    4.08
+16384                   4.63
+32768                   7.55
+65536                  10.07
+131072                 12.15
+262144                 17.37
+524288                 28.50
+1048576                50.04
+2097152                93.27
+4194304               179.65
+```
+
+<b>Test using OSU-Micro-Benchmarks/7.5 with PrgEnv-cray</b>:
+```
+
+hostname:
+gpu-1-111
+gpu-1-102
+
+CPU info:
+Vendor ID:                            ARM
+
+Currently Loaded Modules:
+  1) craype-arm-grace                     7) cray-dsmml/0.3.0
+  2) libfabric/2.3.1                      8) cray-mpich/9.1.0
+  3) craype-network-ofi                   9) cray-libsci/26.03.0
+  4) perftools-base/26.03.0               10) PrgEnv-cray/8.7.0
+  5) xpmem/2.11.3-1.3_gdbda01a1eb3d       11) cuda/13.0
+  6) cce/21.0.0                           12) CrayEnv
+  7) craype/2.7.36
+
+# OSU MPI-CUDA Bi-Directional Bandwidth Test v7.5
+# Datatype: MPI_CHAR.
+# Size      Bandwidth (MB/s)
+1                       1.14
+2                       2.23
+4                       4.56
+8                       9.18
+16                     18.41
+32                     36.77
+64                     74.20
+128                   147.12
+256                   275.37
+512                   569.29
+1024                 1161.92
+2048                 2339.97
+4096                 4640.06
+8192                 9350.01
+16384               18583.90
+32768               23840.66
+65536               34521.83
+131072              39704.04
+262144              41814.18
+524288              44072.94
+1048576             44682.92
+2097152             45122.15
+4194304             45029.99
+
+# OSU MPI-CUDA Latency Test v7.5
+# Datatype: MPI_CHAR.
+# Size       Avg Latency(us)
+1                       3.31
+2                       3.30
+4                       3.24
+8                       3.36
+16                      3.21
+32                      3.36
+64                      3.24
+128                     4.45
+256                     4.43
+512                     4.56
+1024                    4.62
+2048                    4.81
+4096                    4.92
+8192                    5.36
+16384                   6.46
+32768                  10.14
+65536                  11.58
+131072                 14.56
+262144                 19.77
+524288                 31.93
+1048576                56.43
+2097152               102.16
+4194304               181.70
+```
+</details>
+
+## Conclusion
+There is a notable improvement in performance. While additional testing is still required, the current results are highly satisfactory.