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Updated sample shift.
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configs/README.md

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@@ -104,7 +104,7 @@ Configs have the three highest parameter keys:
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| `data`:`format` | `pandas` | `pandas`, `numpy`, `cudf` | Data format to use in benchmark. |
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| `data`:`order` | `F` | `C`, `F` | Data order to use in benchmark: contiguous(C) or Fortran. |
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| `data`:`dtype` | `float64` | | Data type to use in benchmark. |
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| `data`:`distributed_split` | None | None, `rank_based`, `sample_shift` | `rank_based` Split type used to distribute data between machines in distributed algorithm. `sample_shift`: Shift each data point in a rank by \((\sqrt{\text{rank id}} \times 0.003) + 1\). `None` type means usage of all data without split on all machines. `rank_based` type splits the data equally between machines with split sequence based on rank id from MPI. |
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| `data`:`distributed_split` | None | None, `rank_based`, `sample_shift` | `rank_based` Split type used to distribute data between machines in distributed algorithm. `sample_shift`: Shift each data point in each rank by sqrt (rank id) * 0.003) + 1. `None` type means usage of all data without split on all machines. `rank_based` type splits the data equally between machines with split sequence based on rank id from MPI. |
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|<h3>Algorithm parameters</h3>||||
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| `algorithm`:`library` | None | | Python module containing measured entity (class or function). |
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| `algorithm`:`device` | `default` | `default`, `cpu`, `gpu` | Device selected for computation. |

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