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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.
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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.
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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.
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In this follow‑up post, we present the results using OSU-Micro-Benchmarks/7.5 and discuss show how close EESSI can now get to native, vendor‑optimized MPI performance on Slingshot‑11 systems.
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In this followup 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.
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### System Architecture
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@@ -32,9 +32,11 @@ We evaluated two OSU Micro-Benchmark builds:
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The following commands were used to run the benchmarks:
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`mpirun -np 2 osu_bibw D D`
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`srun -N 2 --ntasks-per-node=1 osu_bibw -i 10 D D`
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`mpirun -np 2 osu_latency D D`
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`srun -N 2 --ntasks-per-node=1 osu_latency -i 10 D D`
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