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@Suad0 Suad0 commented Nov 8, 2024

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// Extrapolate if input is outside known range
if input_lengths_sum < anals.first().unwrap().input_lengths.iter().sum::<usize>() {
let lhs = &anals[0];
let rhs = &anals[1];
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At this stage, there could be only a single analyzation in the vector. Therefore, this can panic

let rhs = &anals[1];
return self.extrapolate_and_execute(lhs, rhs, input_lengths_sum, cpu_op, gpu_op);
} else if input_lengths_sum > anals.last().unwrap().input_lengths.iter().sum::<usize>() {
let lhs = &anals[anals.len() - 2];
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same as above

let input_lengths_sum = input_lengths.iter().sum::<usize>();

// Extrapolate if input is outside known range
if input_lengths_sum < anals.first().unwrap().input_lengths.iter().sum::<usize>() {
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There is no chance to add new data points as the interpolation step takes any two analyzations (lhs, rhs) where the new analyzation (x) input size sum is lhs_input_sum <= x_input_sum <= rhs_input_sum.
Hence the max analyzations amount would be 2 ig

let new_cpu_dur = lhs.cpu_dur.as_secs_f32()
+ 0.5 * (rhs.cpu_dur.as_secs_f32() - lhs.cpu_dur.as_secs_f32());
+ (input_lengths_sum - input_lengths_lhs) as f32
/ (input_lengths_rhs - input_lengths_lhs) as f32
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could leave this factor at 0.5

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2 participants