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//use crate::common::validate_inputs;
use crate::common_simd::options::{validate_inputs, validate_options};
use crate::indicators::cmo::{
min_data, output_length, IndicatorState, State, INPUTS_WIDTH, OPTIONS_WIDTH,
};
use crate::indicators::simd_indicators::cmo_simd::{calc_simd, SimdState};
use crate::indicators::simd_indicators::road_train::{Asset, Driver, PrimeMover};
use crate::types::IndicatorError;
use std::simd::Simd;
/// SIMD driver for the Chande Momentum Oscillator (CMO) indicator, processing `N` option-set lanes per scheduling epoch.
struct CmoDriver;
impl Driver<State, usize> for CmoDriver {
/// Processes one epoch of output bars for `N` option-set lanes simultaneously using SIMD. Reads the shared input, applies each lane's options, writes outputs, and updates per-lane states.
fn next_run<const N: usize>(
&mut self,
inputs: Vec<Vec<&[f64]>>,
mut outputs: Vec<Vec<&mut [f64]>>,
mut states: Vec<&mut State>,
options: Vec<Option<&usize>>,
) {
let len = outputs[0][0].len();
let mut i = [0usize; N];
let mut prev_i = [0usize; N];
for (lane, option) in options.iter().enumerate() {
if let Some(&period) = option {
i[lane] = period + 1;
prev_i[lane] = period;
}
}
// Optimization 1: Direct array construction instead of collect+try_into
let mut state = SimdState::new(&states);
// Optimization 2: Pre-compute all input and output pointers
let input_ptrs = crate::extract_input_ptrs!(inputs, N, real_ptrs);
let cmo_line_ptr = crate::extract_output_ptrs!(outputs, N, cmo_line_ptr);
// Optimization 3: Simplified main loop with pre-computed offsets
for j in 0..len {
// Get new and old values using pre-computed pointers
let (current, prev) = crate::extract_simd_at_indices_array!(N, input_ptrs,
current @ i,
prev @ prev_i
);
let (prev_before, prev_period) = crate::extract_simd_at_indices!(N, input_ptrs,
prev_before @ j,
prev_period @ j + 1
);
let cmo = calc_simd(&mut state, prev_before, prev_period, current, prev);
// Store results using pre-computed pointers
crate::write_simd_at_indices!(N, j,
cmo_line_ptr => cmo
);
prev_i = i;
for i in i.iter_mut() {
*i += 1;
}
}
state.write_states(&mut states);
}
}
/// Calculates the Chande Momentum Oscillator (CMO) on a single asset with `N` different option sets
/// simultaneously using SIMD parallelism.
///
/// # Arguments
/// * `inputs` - The single asset's price series (`[&[f64]; INPUTS_WIDTH]`), containing
/// `[real]`.
/// * `options` - An array of `N` option sets, one per SIMD lane: `[period]`.
/// * `optional_outputs` - Unused; CMO has no optional outputs.
///
/// # Returns
/// `Ok((outputs, states))` where `outputs[i]` contains `[cmo]`
/// and `states[i]` is the final [`IndicatorState`] for option set `i`.
/// Returns `Err(IndicatorError)` if inputs are too short or options are invalid.
pub fn indicator_by_options<const N: usize>(
inputs: &[&[f64]; INPUTS_WIDTH], //stock[ fields [ field [f64] ] ]
options: &[&[f64; OPTIONS_WIDTH]; N],
_optional_outputs: Option<&[bool]>,
) -> Result<(Vec<Vec<Vec<f64>>>, Vec<IndicatorState>), IndicatorError> {
validate_inputs::<OPTIONS_WIDTH>(inputs, options, min_data)?;
validate_options(options, None)?;
let mut road_train = PrimeMover::<N, State, usize>::new();
let mut params = [0usize; N];
for i in 0..N {
params[i] = options[i][0] as usize;
}
let mut output_buffers = Vec::with_capacity(N);
for i in 0..N {
let period = options[i][0] as usize;
let asset_inputs = vec![
inputs[0], // real
];
let cmo_line = {
let capacity = output_length(inputs[0].len(), options[i]);
crate::uninit_vec!(f64, capacity)
};
let state = State::init_state(inputs[0], period);
let mut output_buffer = vec![cmo_line];
//let adosc_len = output_buffer[0].len();
let mut asset_outputs = Vec::with_capacity(output_buffer.len());
for j in 0..output_buffer.len() {
unsafe {
//let slice_len = output_buffer.len() - starts[j];
// Get a mutable reference to the output buffer for this asset
let output_buffer = &mut output_buffer[j];
asset_outputs.push(std::slice::from_raw_parts_mut(
output_buffer.as_mut_ptr(), //slice from
output_buffer.len(), // slice to
));
}
}
road_train.add_asset(Asset::new(
asset_inputs,
asset_outputs,
i,
period,
period + 1,
state,
Some(¶ms[i]),
));
output_buffers.push(output_buffer);
}
let mut driver = CmoDriver {};
let states_vec = road_train.drive(&mut driver);
let mut states = Vec::with_capacity(N);
for (i, state) in states_vec.into_iter().enumerate() {
states.push(IndicatorState::new(inputs[0], state, params[i]));
}
Ok((output_buffers, states))
}