wrong power of two
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## Benchmarks details
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## Benchmarks details
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- Create in memory a list of `N=128` one dimensional numpy arrays of length `L` starting from `L=2` up to `L=2²³=4_194_304` in steps of powers of two.
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- Create in memory a list of `N=128` one dimensional numpy arrays of length `L` starting from `L=2` up to `L=2²²=4_194_304` in steps of powers of two.
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- Given that each item of the array is of type `float64`, i.e. 8 bytes, the size of the arrays goes from `16B` to `32M`
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- Given that each item of the array is of type `float64`, i.e. 8 bytes, the size of the arrays goes from `16B` to `32M`
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- The total memory required is at least `128 × 32M × 2 = 8G`
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- The total memory required is at least `128 × 32M × 2 = 8G`
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- Load the whole list in one big numpy array of size `N`x`L` (*good*) and `L`x`N` (*bad*). The corresponding loops are:
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- Load the whole list in one big numpy array of size `N`x`L` (*good*) and `L`x`N` (*bad*). The corresponding loops are:
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