CUDA-aware fit engine for analytic single pulse fits. More...

#include <jacobian_analytic.h>

Inheritance diagram for ddastoys::analyticfit::CudaFitEngine1:

Collaboration diagram for ddastoys::analyticfit::CudaFitEngine1:

Public Member Functions
	CudaFitEngine1 (std::vector< std::pair< uint16_t, uint16_t >> &data)
	Constructor. More...

	~CudaFitEngine1 ()
	Destructor. More...

virtual void	jacobian (const gsl_vector p, gsl_matrix J)
	Invoke the kernal to do the pointwise parallel Jacobian computation. More...

virtual void	residuals (const gsl_vector p, gsl_vector r)
	Triggers a pointwise parallel residual kernel in the device and impedance matches that with GSL's requirements. More...

Public Member Functions inherited from ddastoys::CFitEngine
	CFitEngine (std::vector< std::pair< uint16_t, uint16_t >> &data)
	Constructor. More...

virtual	~CFitEngine ()
	Destructor.

Additional Inherited Members
Protected Attributes inherited from ddastoys::CFitEngine
std::vector< uint16_t >	x
	Trace x coordinate vector.

std::vector< uint16_t >	y
	Trace y coordinate vector.

Detailed Description

CUDA-aware fit engine for analytic single pulse fits.

The concept is that each GSL lmfitter can supply a pair of methods: One that computes a vector of residuals and one that computes a Jacobian matrix of partial derivatives. At the implementation level we have two types of fits we need done: Single pulse fits and double pulse fits (the engines with names ending in 1 or 2). For each fit type we have two fit engines: 1) Serial computation (the engines with names starting with Serial) 2) GPU accelerated (the engines with names starting with Cuda).

Finally a fit factory can generate the appropriate fit engine as desired by the actual fit.

Todo:: (ASC 10/30/23): Manages some device pointers. Not copyable, and most likely is not ever copied. But we can make it safe.

Constructor & Destructor Documentation

◆ CudaFitEngine1()

ddastoys::analyticfit::CudaFitEngine1::CudaFitEngine1 ( std::vector< std::pair< uint16_t, uint16_t >> & data )

Constructor.

Allocate the device vectors/matrices. Push the trace x/y points into the GPU where they stay until we're destroyed.

◆ ~CudaFitEngine1()

ddastoys::analyticfit::CudaFitEngine1::~CudaFitEngine1 ( )

Destructor.

Just deallocate the GPU resources.

Member Function Documentation

◆ jacobian()

void ddastoys::analyticfit::CudaFitEngine1::jacobian	(	const gsl_vector *	p,
		gsl_matrix *	J
	)

virtual

Invoke the kernal to do the pointwise parallel Jacobian computation.

Parameters

p	Parameter vector.
J	Jacobian matrix.

We use a Y size of 32 and x size of npts+31/32. That is one warp wide.

Implements ddastoys::CFitEngine.

◆ residuals()

void ddastoys::analyticfit::CudaFitEngine1::residuals	(	const gsl_vector *	p,
		gsl_vector *	r
	)