Profiling results for top pair plus jets production with Pepper v1.1.1

Profiling results for top pair plus jets production with Pepper v1.1.1

Contents

This includes data/output for the following GPU accelerated unweighted event generation runs:

A run over a few seconds to produce pepper-internal timing results (`*timers.csv` files)

The same run, but with `nvprof` (`*.nvprof` files)

A run with a single event batch, with `ncu --import-source on --set full` (`*.ncu-rep` files)

The simulated process is top pair production with n jets, with n = 0...4, at 13 TeV. The configuration files (`pepper.ini`) are included. Also the `pepper_cache` directories are included.

All results are for the "main" pepper variant (which uses Kokkos to utilise the GPU) and for the "native" pepper variant (which uses CUDA directly).

Software stack and CPU/GPU hardware details

The software/hardware used for the profiling are as follows:

GPU Driver: NVIDIA-SMI: 550.100, Driver Version: 550.100, CUDA Version: 12.4

GPU: Tesla V100S-PCIE-32GB

Cuda compilation tools: release 11.6, V11.6.124

Kokkos 4.3.01

gcc (GCC) 11.4.1 20231218 (Red Hat 11.4.1-3)

Intel(R) Xeon(R) Silver 4214R CPU @ 2.40GHz

Note that the event generation includes write-out of event files. The LHEH5 files are written to local SSD storage. The event files are not included in this dataset.

Additional run parameters

TTBar
number of batches
batch size
rate (main variant)
rate (native variant)

+0j
20
1,179,648
1.4e10
2.0e10

+1j
20
1,179,648
1.5e10
2.4e10

+2j
20
1,179,648 * 2
1.3e10
2.7e10

+3j
20
1,179,648 / 2
6.4e9
1.4e10

+4j
20
1,179,648
2.2e9
2.2e9

The number of batches has been chosen such that the most important sub processes are likely to be sampled and such that the overall runtime is at least a few seconds. The batch size has been chosen by scanning over factors of two and picking the best-performing batch size with the native variant. The event rate is the number given in the Pepper output. It does not include the closing time of the generated HDF5 file, which can be significant for the two lowest multiplicities. This can be checked by inspecting the corresponding relative and absolute timing results in the `*timing.csv` files included in the dataset.