Struct DeviceResidentArrowWorkspace 

pub struct DeviceResidentArrowWorkspace { /* private fields */ }

Upload-once workspace for the SAE data-fit Arrow-Schur inner iteration.

Implementations

impl DeviceResidentArrowWorkspace

pub fn new( shape: DeviceResidentArrowShape, target_x: Vec<f64>, basis_values: Vec<f64>, gate_activations: Vec<f64>, slabs: DeviceResidentArrowSlabs, ) -> Result<Self, DeviceResidentArrowError>

pub const fn shape(&self) -> DeviceResidentArrowShape

pub fn device_resident(&self) -> bool

pub fn resident_device_bytes(&self) -> usize

pub fn host_shadow_bytes(&self) -> usize

pub fn one_inner_iteration( &self, ridge_t: f64, ridge_beta: f64, ) -> Result<DeviceResidentArrowStep, DeviceResidentArrowError>

Run one device-side Newton sequence. No CPU fallback is attempted here: callers that want a reference path must call Self::cpu_reference_step.

pub fn cpu_reference_step( &self, ridge_t: f64, ridge_beta: f64, ) -> Result<DeviceResidentArrowStep, DeviceResidentArrowError>

CPU reference for parity harnesses. This path is explicit and is never called from Self::one_inner_iteration.

pub fn to_arrow_system(&self) -> ArrowSchurSystem

pub fn device_fit( &self, opts: &DeviceResidentInnerOptions, ) -> Result<DeviceResidentInnerOutcome, DeviceResidentArrowError>

Run the full device-resident inner Newton loop. Routes the per-iteration arrow solve through the GPU path; returns Unavailable when CUDA did not admit the resident workload (callers wanting a CPU path use Self::cpu_reference_fit).

pub fn device_reupload_fit( &self, opts: &DeviceResidentInnerOptions, ) -> Result<DeviceResidentInnerOutcome, DeviceResidentArrowError>

The #1017 residency baseline: run the SAME inner Newton loop but compute each per-iterate arrow step through solve_arrow_newton_step, which re-packs/re-uploads D/B/g and re-runs the per-row POTRF + border Schur factor on EVERY iterate. This is the “current re-uploading path”; the bench divides Self::device_fit (resident) against it to isolate the across-iteration residency speedup on one device, holding the host control flow and the GPU factor kernels fixed.

pub fn cpu_reference_fit( &self, opts: &DeviceResidentInnerOptions, ) -> Result<DeviceResidentInnerOutcome, DeviceResidentArrowError>

CPU dense-reference inner loop. Bit-for-bit the same host arithmetic as Self::device_fit except the per-iteration arrow solve uses the dense reference factorisation; the parity harness asserts the two agree.

pub fn device_fit_outer_sequence( &self, base_gradient_overrides: &[(Vec<f64>, Vec<f64>)], opts: &DeviceResidentInnerOptions, ) -> Result<OuterSequenceOutcome, DeviceResidentArrowError>

Run a sequence of outer evaluations that SHARE one resident frame when the Hessian operator is unchanged across outers (#1017 deliverable 3).

Each entry of base_gradient_overrides is one outer evaluation’s base gradient (g_t rows: n·d, g_β: p) — the only part of the bordered quadratic that moves across outers at a frozen gate/basis frame. The constant Hessian blocks ride the resident frame, which is built ONCE and reused for every outer (frame builds are counted and returned so a caller can assert the across-outer amortization actually fired: exactly one frame build for an unchanged operator, regardless of how many outers run).

Returns one DeviceResidentInnerOutcome per outer plus the number of resident-frame builds performed across the whole sweep. On a CPU-only host returns Unavailable (callers wanting a host path use Self::cpu_reference_outer_sequence).

pub fn cpu_reference_outer_sequence( &self, base_gradient_overrides: &[(Vec<f64>, Vec<f64>)], opts: &DeviceResidentInnerOptions, ) -> Result<OuterSequenceOutcome, DeviceResidentArrowError>

CPU-reference outer sequence: same host control flow as Self::device_fit_outer_sequence but the per-iterate arrow solve uses the dense reference factorisation. The parity harness asserts the device across-outer sweep agrees with this per-outer-independent reference.