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Hi,
I ran "getri.cpp" (oneAPI base toolkit examples @ /opt/intel/oneapi/mkl/2023.0.0/examples/examples_dpcpp.tgz.) through the Intel Advisor to compare CPU to GPU offload analysis. It seems my old Xeon processor can do it as fast as a data center GPU Ponte Vecchio XT 512 XVE. Any idea?
Selected accelerator to analyze: Intel(R) Ponte Vecchio XT 512 XVE.
Baseline Host: Intel(R) Xeon(R) W-3225 CPU @ 3.70GHz.
Measured CPU Time: 4.520s Accelerated CPU+GPU Time: 4.520s
Speedup for Accelerated Code: 1.0x Number of Offloads: 0 Fraction of Accelerated Code: 0%
Compile and link settings
icpx -fsycl -fsycl-device-code-split=per_kernel -DMKL_ILP64 -I$MKLROOT/include -L$MKLROOT/lib/intel64 -DSYCL_DEVICES_cpu -lmkl_sycl -lmkl_intel_ilp64 -lmkl_sequential -lmkl_core -lsycl -lOpenCL -lpthread -lm -ldl -O2 -g getri.cpp -o getri
Advisor CLIs
advisor --collect=survey --auto-finalize --static-instruction-mix --project-dir=./getri_run512 -- ./getri
advisor --collect=tripcounts --flop --stacks --auto-finalize --cache-simulation=single --data-transfer=light --target-device=pvc_xt_512xve --project-dir=./getri_run512 -- ./getri
advisor --collect=projection --no-assume-dependencies --config=pvc_xt_512xve --project-dir=./getri_run512 -- ./getri
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Hello,
That's right - Offload Modeling shows the same performance on PVC for this sample. Do you have PVC results as well? Could you please share them?
Best regards,
Ruslan Murtazin
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Hi Ruslan,
Do you mean the results on actual PVC GPU or any other PVC results generated by the intel advisor? Can you please be specific?
Thanks.
Rajitha
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Hi Rajitha,
Yes, exactly! I meant Advisor GPU profiling result for the same app (but gathered on real PVC) to compare against Offload Modeling result.
Best regards,
Ruslan
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Hi,
We haven't received any response from your end. Is your issue resolved?
Regards,
Remya Premdas
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Hi,
We assume that your issue is resolved. If you need any additional information, please post a new question as this thread will no longer be monitored by Intel.
Regards,
Remya Premdas

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