| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620621622623624625626627628629630631632633634635636637638639640641642643644645646647648649650651652653654655656657658659660661662663664665666667668669670671672673674675676677678679680681682683684685686687688689690691692693694695696697698699700701702703704705706707708709710711712713714715716717718719720721722723724725726727728729730731732733734735736737738739740741742743744745746747748749750751752753754755756757758759760761762763764765766767768769770771772773774775776777778779780781782783784785786787788789790791792793794795796797798799800801802803804805806807808809810811812813814815816817818819820821822823824825826827828829830831832833834835836837838839840841842843844845846847848849850851852853854855856857858859860861862863864865866867868869870871872 | /* StarPU --- Runtime system for heterogeneous multicore architectures. * * Copyright (C) 2009-2013  Université de Bordeaux 1 * Copyright (C) 2010, 2011, 2012, 2013  Centre National de la Recherche Scientifique * * StarPU is free software; you can redistribute it and/or modify * it under the terms of the GNU Lesser General Public License as published by * the Free Software Foundation; either version 2.1 of the License, or (at * your option) any later version. * * StarPU is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. * * See the GNU Lesser General Public License in COPYING.LGPL for more details. *//* * * Dumb parallel version * */#define DIV_1D 64  /*   * Overall strategy for an fft of size n:   * - perform n1 ffts of size n2   * - twiddle   * - perform n2 ffts of size n1   *   * - n1 defaults to DIV_1D, thus n2 defaults to n / DIV_1D.   *   * Precise tasks:   *   * - twist1: twist the whole n-element input (called "in") into n1 chunks of   *           size n2, by using n1 tasks taking the whole n-element input as a   *           R parameter and one n2 output as a W parameter. The result is   *           called twisted1.   * - fft1:   perform n1 (n2) ffts, by using n1 tasks doing one fft each. Also   *           twiddle the result to prepare for the fft2. The result is called   *           fft1.   * - join:   depends on all the fft1s, to gather the n1 results of size n2 in   *           the fft1 vector.   * - twist2: twist the fft1 vector into n2 chunks of size n1, called twisted2.   *           since n2 is typically very large, this step is divided in DIV_1D   *           tasks, each of them performing n2/DIV_1D of them   * - fft2:   perform n2 ffts of size n1. This is divided in DIV_1D tasks of   *           n2/DIV_1D ffts, to be performed in batches. The result is called   *           fft2.   * - twist3: twist back the result of the fft2s above into the output buffer.   *           Only implemented on CPUs for simplicity of the gathering.   *   * The tag space thus uses 3 dimensions:   * - the number of the plan.   * - the step (TWIST1, FFT1, JOIN, TWIST2, FFT2, TWIST3, END)   * - an index i between 0 and DIV_1D-1.   */#define STEP_TAG_1D(plan, step, i) _STEP_TAG(plan, step, i)#ifdef __STARPU_USE_CUDA/* twist1: * * Twist the full input vector (first parameter) into one chunk of size n2 * (second parameter) */static voidSTARPUFFT(twist1_1d_kernel_gpu)(void *descr[], void *_args){	struct STARPUFFT(args) *args = _args;	STARPUFFT(plan) plan = args->plan;	int i = args->i;	int n1 = plan->n1[0];	int n2 = plan->n2[0];	_cufftComplex * restrict in = (_cufftComplex *)STARPU_VECTOR_GET_PTR(descr[0]);	_cufftComplex * restrict twisted1 = (_cufftComplex *)STARPU_VECTOR_GET_PTR(descr[1]);		STARPUFFT(cuda_twist1_1d_host)(in, twisted1, i, n1, n2);	cudaStreamSynchronize(starpu_cuda_get_local_stream());}/* fft1: * * Perform one fft of size n2 */static voidSTARPUFFT(fft1_1d_plan_gpu)(void *args){	STARPUFFT(plan) plan = args;	int n2 = plan->n2[0];	int workerid = starpu_worker_get_id();	cufftResult cures;	cures = cufftPlan1d(&plan->plans[workerid].plan1_cuda, n2, _CUFFT_C2C, 1);	if (cures != CUFFT_SUCCESS)		STARPU_CUFFT_REPORT_ERROR(cures);	cufftSetStream(plan->plans[workerid].plan1_cuda, starpu_cuda_get_local_stream());	if (cures != CUFFT_SUCCESS)		STARPU_CUFFT_REPORT_ERROR(cures);}static voidSTARPUFFT(fft1_1d_kernel_gpu)(void *descr[], void *_args){	struct STARPUFFT(args) *args = _args;	STARPUFFT(plan) plan = args->plan;	int i = args->i;	int n2 = plan->n2[0];	cufftResult cures;	_cufftComplex * restrict in = (_cufftComplex *)STARPU_VECTOR_GET_PTR(descr[0]);	_cufftComplex * restrict out = (_cufftComplex *)STARPU_VECTOR_GET_PTR(descr[1]);	const _cufftComplex * restrict roots = (_cufftComplex *)STARPU_VECTOR_GET_PTR(descr[2]);	int workerid = starpu_worker_get_id();	task_per_worker[workerid]++;	cures = _cufftExecC2C(plan->plans[workerid].plan1_cuda, in, out, plan->sign == -1 ? CUFFT_FORWARD : CUFFT_INVERSE);	if (cures != CUFFT_SUCCESS)		STARPU_CUFFT_REPORT_ERROR(cures);	STARPUFFT(cuda_twiddle_1d_host)(out, roots, n2, i);	cudaStreamSynchronize(starpu_cuda_get_local_stream());}/* fft2: * * Perform n3 = n2/DIV_1D ffts of size n1 */static voidSTARPUFFT(fft2_1d_plan_gpu)(void *args){	STARPUFFT(plan) plan = args;	int n1 = plan->n1[0];	int n2 = plan->n2[0];	int n3 = n2/DIV_1D;	cufftResult cures;	int workerid = starpu_worker_get_id();	cures = cufftPlan1d(&plan->plans[workerid].plan2_cuda, n1, _CUFFT_C2C, n3);	if (cures != CUFFT_SUCCESS)		STARPU_CUFFT_REPORT_ERROR(cures);	cufftSetStream(plan->plans[workerid].plan2_cuda, starpu_cuda_get_local_stream());	if (cures != CUFFT_SUCCESS)		STARPU_CUFFT_REPORT_ERROR(cures);}static voidSTARPUFFT(fft2_1d_kernel_gpu)(void *descr[], void *_args){	struct STARPUFFT(args) *args = _args;	STARPUFFT(plan) plan = args->plan;	cufftResult cures;	_cufftComplex * restrict in = (_cufftComplex *)STARPU_VECTOR_GET_PTR(descr[0]);	_cufftComplex * restrict out = (_cufftComplex *)STARPU_VECTOR_GET_PTR(descr[1]);	int workerid = starpu_worker_get_id();	task_per_worker[workerid]++;	/* NOTE using batch support */	cures = _cufftExecC2C(plan->plans[workerid].plan2_cuda, in, out, plan->sign == -1 ? CUFFT_FORWARD : CUFFT_INVERSE);	if (cures != CUFFT_SUCCESS)		STARPU_CUFFT_REPORT_ERROR(cures);	cudaStreamSynchronize(starpu_cuda_get_local_stream());}#endif/* twist1: * * Twist the full input vector (first parameter) into one chunk of size n2 * (second parameter) */static voidSTARPUFFT(twist1_1d_kernel_cpu)(void *descr[], void *_args){	struct STARPUFFT(args) *args = _args;	STARPUFFT(plan) plan = args->plan;	int i = args->i;	int j;	int n1 = plan->n1[0];	int n2 = plan->n2[0];	STARPUFFT(complex) * restrict in = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[0]);	STARPUFFT(complex) * restrict twisted1 = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[1]);	/* printf("twist1 %d %g\n", i, (double) cabs(plan->in[i])); */	for (j = 0; j < n2; j++)		twisted1[j] = in[i+j*n1];}#ifdef STARPU_HAVE_FFTW/* fft1: * * Perform one fft of size n2 */static voidSTARPUFFT(fft1_1d_kernel_cpu)(void *descr[], void *_args){	struct STARPUFFT(args) *args = _args;	STARPUFFT(plan) plan = args->plan;	int i = args->i;	int j;	int n2 = plan->n2[0];	int workerid = starpu_worker_get_id();	task_per_worker[workerid]++;	STARPUFFT(complex) * restrict twisted1 = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[0]);	STARPUFFT(complex) * restrict fft1 = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[1]);	/* printf("fft1 %d %g\n", i, (double) cabs(twisted1[0])); */	_FFTW(execute_dft)(plan->plans[workerid].plan1_cpu, twisted1, fft1);	/* twiddle fft1 buffer */	for (j = 0; j < n2; j++)		fft1[j] = fft1[j] * plan->roots[0][i*j];}#endif/* twist2: * * Twist the full vector (results of the fft1s) into one package of n2/DIV_1D * chunks of size n1 */static voidSTARPUFFT(twist2_1d_kernel_cpu)(void *descr[], void *_args){	struct STARPUFFT(args) *args = _args;	STARPUFFT(plan) plan = args->plan;	int jj = args->jj;	/* between 0 and DIV_1D */	int jjj;		/* beetween 0 and n3 */	int i;	int n1 = plan->n1[0];	int n2 = plan->n2[0];	int n3 = n2/DIV_1D;	STARPUFFT(complex) * restrict twisted2 = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[0]);	/* printf("twist2 %d %g\n", jj, (double) cabs(plan->fft1[jj])); */	for (jjj = 0; jjj < n3; jjj++) {		int j = jj * n3 + jjj;		for (i = 0; i < n1; i++)			twisted2[jjj*n1+i] = plan->fft1[i*n2+j];	}}#ifdef STARPU_HAVE_FFTW/* fft2: * * Perform n3 = n2/DIV_1D ffts of size n1 */static voidSTARPUFFT(fft2_1d_kernel_cpu)(void *descr[], void *_args){	struct STARPUFFT(args) *args = _args;	STARPUFFT(plan) plan = args->plan;	/* int jj = args->jj; */	int workerid = starpu_worker_get_id();	task_per_worker[workerid]++;	STARPUFFT(complex) * restrict twisted2 = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[0]);	STARPUFFT(complex) * restrict fft2 = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[1]);	/* printf("fft2 %d %g\n", jj, (double) cabs(twisted2[plan->totsize4-1])); */	_FFTW(execute_dft)(plan->plans[workerid].plan2_cpu, twisted2, fft2);}#endif/* twist3: * * Spread the package of n2/DIV_1D chunks of size n1 into the output vector */static voidSTARPUFFT(twist3_1d_kernel_cpu)(void *descr[], void *_args){	struct STARPUFFT(args) *args = _args;	STARPUFFT(plan) plan = args->plan;	int jj = args->jj;	/* between 0 and DIV_1D */	int jjj;		/* beetween 0 and n3 */	int i;	int n1 = plan->n1[0];	int n2 = plan->n2[0];	int n3 = n2/DIV_1D;	const STARPUFFT(complex) * restrict fft2 = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[0]);	/* printf("twist3 %d %g\n", jj, (double) cabs(fft2[0])); */	for (jjj = 0; jjj < n3; jjj++) {		int j = jj * n3 + jjj;		for (i = 0; i < n1; i++)			plan->out[i*n2+j] = fft2[jjj*n1+i];	}}/* Performance models for the 5 kinds of tasks */static struct starpu_perfmodel STARPUFFT(twist1_1d_model) = {	.type = STARPU_HISTORY_BASED,	.symbol = TYPE"twist1_1d"};static struct starpu_perfmodel STARPUFFT(fft1_1d_model) = {	.type = STARPU_HISTORY_BASED,	.symbol = TYPE"fft1_1d"};static struct starpu_perfmodel STARPUFFT(twist2_1d_model) = {	.type = STARPU_HISTORY_BASED,	.symbol = TYPE"twist2_1d"};static struct starpu_perfmodel STARPUFFT(fft2_1d_model) = {	.type = STARPU_HISTORY_BASED,	.symbol = TYPE"fft2_1d"};static struct starpu_perfmodel STARPUFFT(twist3_1d_model) = {	.type = STARPU_HISTORY_BASED,	.symbol = TYPE"twist3_1d"};/* codelet pointers for the 5 kinds of tasks */static struct starpu_codelet STARPUFFT(twist1_1d_codelet) = {	.where =#ifdef __STARPU_USE_CUDA		STARPU_CUDA|#endif		STARPU_CPU,#ifdef __STARPU_USE_CUDA	.cuda_funcs = {STARPUFFT(twist1_1d_kernel_gpu), NULL},#endif	.cpu_funcs = {STARPUFFT(twist1_1d_kernel_cpu), NULL},	CAN_EXECUTE	.model = &STARPUFFT(twist1_1d_model),	.nbuffers = 2,	.modes = {STARPU_R, STARPU_W},	.name = "twist1_1d_codelet"};static struct starpu_codelet STARPUFFT(fft1_1d_codelet) = {	.where =#ifdef __STARPU_USE_CUDA		STARPU_CUDA|#endif#ifdef STARPU_HAVE_FFTW		STARPU_CPU|#endif		0,#ifdef __STARPU_USE_CUDA	.cuda_funcs = {STARPUFFT(fft1_1d_kernel_gpu), NULL},#endif#ifdef STARPU_HAVE_FFTW	.cpu_funcs = {STARPUFFT(fft1_1d_kernel_cpu), NULL},#endif	CAN_EXECUTE	.model = &STARPUFFT(fft1_1d_model),	.nbuffers = 3,	.modes = {STARPU_R, STARPU_W, STARPU_R},	.name = "fft1_1d_codelet"};static struct starpu_codelet STARPUFFT(twist2_1d_codelet) = {	.where = STARPU_CPU,	.cpu_funcs = {STARPUFFT(twist2_1d_kernel_cpu), NULL},	CAN_EXECUTE	.model = &STARPUFFT(twist2_1d_model),	.nbuffers = 1,	.modes = {STARPU_W},	.name = "twist2_1d_codelet"};static struct starpu_codelet STARPUFFT(fft2_1d_codelet) = {	.where =#ifdef __STARPU_USE_CUDA		STARPU_CUDA|#endif#ifdef STARPU_HAVE_FFTW		STARPU_CPU|#endif		0,#ifdef __STARPU_USE_CUDA	.cuda_funcs = {STARPUFFT(fft2_1d_kernel_gpu), NULL},#endif#ifdef STARPU_HAVE_FFTW	.cpu_funcs = {STARPUFFT(fft2_1d_kernel_cpu), NULL},#endif	CAN_EXECUTE	.model = &STARPUFFT(fft2_1d_model),	.nbuffers = 2,	.modes = {STARPU_R, STARPU_W},	.name = "fft2_1d_codelet"};static struct starpu_codelet STARPUFFT(twist3_1d_codelet) = {	.where = STARPU_CPU,	.cpu_funcs = {STARPUFFT(twist3_1d_kernel_cpu), NULL},	CAN_EXECUTE	.model = &STARPUFFT(twist3_1d_model),	.nbuffers = 1,	.modes = {STARPU_R},	.name = "twist3_1d_codelet"};/* * * Sequential version * */#ifdef __STARPU_USE_CUDA/* Perform one fft of size n */static voidSTARPUFFT(fft_1d_plan_gpu)(void *args){	STARPUFFT(plan) plan = args;	cufftResult cures;	int n = plan->n[0];	int workerid = starpu_worker_get_id();	cures = cufftPlan1d(&plan->plans[workerid].plan_cuda, n, _CUFFT_C2C, 1);	if (cures != CUFFT_SUCCESS)		STARPU_CUFFT_REPORT_ERROR(cures);	cufftSetStream(plan->plans[workerid].plan_cuda, starpu_cuda_get_local_stream());	if (cures != CUFFT_SUCCESS)		STARPU_CUFFT_REPORT_ERROR(cures);}static voidSTARPUFFT(fft_1d_kernel_gpu)(void *descr[], void *args){	STARPUFFT(plan) plan = args;	cufftResult cures;	_cufftComplex * restrict in = (_cufftComplex *)STARPU_VECTOR_GET_PTR(descr[0]);	_cufftComplex * restrict out = (_cufftComplex *)STARPU_VECTOR_GET_PTR(descr[1]);	int workerid = starpu_worker_get_id();	task_per_worker[workerid]++;	cures = _cufftExecC2C(plan->plans[workerid].plan_cuda, in, out, plan->sign == -1 ? CUFFT_FORWARD : CUFFT_INVERSE);	if (cures != CUFFT_SUCCESS)		STARPU_CUFFT_REPORT_ERROR(cures);	cudaStreamSynchronize(starpu_cuda_get_local_stream());}#endif#ifdef STARPU_HAVE_FFTW/* Perform one fft of size n */static voidSTARPUFFT(fft_1d_kernel_cpu)(void *descr[], void *_args){	STARPUFFT(plan) plan = _args;	int workerid = starpu_worker_get_id();	task_per_worker[workerid]++;	STARPUFFT(complex) * restrict in = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[0]);	STARPUFFT(complex) * restrict out = (STARPUFFT(complex) *)STARPU_VECTOR_GET_PTR(descr[1]);	_FFTW(execute_dft)(plan->plans[workerid].plan_cpu, in, out);}#endifstatic struct starpu_perfmodel STARPUFFT(fft_1d_model) = {	.type = STARPU_HISTORY_BASED,	.symbol = TYPE"fft_1d"};static struct starpu_codelet STARPUFFT(fft_1d_codelet) = {	.where =#ifdef __STARPU_USE_CUDA		STARPU_CUDA|#endif#ifdef STARPU_HAVE_FFTW		STARPU_CPU|#endif		0,#ifdef __STARPU_USE_CUDA	.cuda_funcs = {STARPUFFT(fft_1d_kernel_gpu), NULL},#endif#ifdef STARPU_HAVE_FFTW	.cpu_funcs = {STARPUFFT(fft_1d_kernel_cpu), NULL},#endif	CAN_EXECUTE	.model = &STARPUFFT(fft_1d_model),	.nbuffers = 2,	.modes = {STARPU_R, STARPU_W},	.name = "fft_1d_codelet"};/* Planning: * * - For each CPU worker, we need to plan the two fftw stages. * - For GPU workers, we need to do the planning in the CUDA context, so we do *   this lazily through the initialised1 and initialised2 flags ; TODO: use *   starpu_execute_on_each_worker instead (done in the omp branch). * - We allocate all the temporary buffers and register them to starpu. * - We create all the tasks, but do not submit them yet. It will be possible *   to reuse them at will to perform several ffts with the same planning. */STARPUFFT(plan)STARPUFFT(plan_dft_1d)(int n, int sign, unsigned flags){	int workerid;	int n1 = DIV_1D;	int n2 = n / n1;	int n3;	int z;	struct starpu_task *task;if (PARALLEL) {#ifdef __STARPU_USE_CUDA	/* cufft 1D limited to 8M elements */	while (n2 > 8 << 20) {		n1 *= 2;		n2 /= 2;	}#endif	STARPU_ASSERT(n == n1*n2);	STARPU_ASSERT(n1 < (1ULL << I_BITS));	/* distribute the n2 second ffts into DIV_1D packages */	n3 = n2 / DIV_1D;	STARPU_ASSERT(n2 == n3*DIV_1D);}	/* TODO: flags? Automatically set FFTW_MEASURE on calibration? */	STARPU_ASSERT(flags == 0);	STARPUFFT(plan) plan = malloc(sizeof(*plan));	memset(plan, 0, sizeof(*plan));if (PARALLEL) {	plan->number = STARPU_ATOMIC_ADD(&starpufft_last_plan_number, 1) - 1;	/* The plan number has a limited size */	STARPU_ASSERT(plan->number < (1ULL << NUMBER_BITS));}	/* Just one dimension */	plan->dim = 1;	plan->n = malloc(plan->dim * sizeof(*plan->n));	plan->n[0] = n;if (PARALLEL) {	check_dims(plan);	plan->n1 = malloc(plan->dim * sizeof(*plan->n1));	plan->n1[0] = n1;	plan->n2 = malloc(plan->dim * sizeof(*plan->n2));	plan->n2[0] = n2;}	/* Note: this is for coherency with the 2D case */	plan->totsize = n;if (PARALLEL) {	plan->totsize1 = n1;	plan->totsize2 = n2;	plan->totsize3 = DIV_1D;	plan->totsize4 = plan->totsize / plan->totsize3;}	plan->type = C2C;	plan->sign = sign;if (PARALLEL) {	/* Compute the w^k just once. */	compute_roots(plan);}	/* Initialize per-worker working set */	for (workerid = 0; workerid < starpu_worker_get_count(); workerid++) {		switch (starpu_worker_get_type(workerid)) {		case STARPU_CPU_WORKER:#ifdef STARPU_HAVE_FFTWif (PARALLEL) {			/* first fft plan: one fft of size n2.			 * FFTW imposes that buffer pointers are known at			 * planning time. */			plan->plans[workerid].plan1_cpu = _FFTW(plan_dft_1d)(n2, NULL, (void*) 1, sign, _FFTW_FLAGS);			STARPU_ASSERT(plan->plans[workerid].plan1_cpu);			/* second fft plan: n3 ffts of size n1 */			plan->plans[workerid].plan2_cpu = _FFTW(plan_many_dft)(plan->dim,					plan->n1, n3,					NULL, NULL, 1, plan->totsize1,					(void*) 1, NULL, 1, plan->totsize1,					sign, _FFTW_FLAGS);			STARPU_ASSERT(plan->plans[workerid].plan2_cpu);} else {			/* fft plan: one fft of size n. */			plan->plans[workerid].plan_cpu = _FFTW(plan_dft_1d)(n, NULL, (void*) 1, sign, _FFTW_FLAGS);			STARPU_ASSERT(plan->plans[workerid].plan_cpu);}#else/* #warning libstarpufft can not work correctly if libfftw3 is not installed */#endif			break;		case STARPU_CUDA_WORKER:			break;		default:			/* Do not care, we won't be executing anything there. */			break;		}	}#ifdef __STARPU_USE_CUDAif (PARALLEL) {	starpu_execute_on_each_worker(STARPUFFT(fft1_1d_plan_gpu), plan, STARPU_CUDA);	starpu_execute_on_each_worker(STARPUFFT(fft2_1d_plan_gpu), plan, STARPU_CUDA);} else {	starpu_execute_on_each_worker(STARPUFFT(fft_1d_plan_gpu), plan, STARPU_CUDA);}#endifif (PARALLEL) {	/* Allocate buffers. */	plan->twisted1 = STARPUFFT(malloc)(plan->totsize * sizeof(*plan->twisted1));	memset(plan->twisted1, 0, plan->totsize * sizeof(*plan->twisted1));	plan->fft1 = STARPUFFT(malloc)(plan->totsize * sizeof(*plan->fft1));	memset(plan->fft1, 0, plan->totsize * sizeof(*plan->fft1));	plan->twisted2 = STARPUFFT(malloc)(plan->totsize * sizeof(*plan->twisted2));	memset(plan->twisted2, 0, plan->totsize * sizeof(*plan->twisted2));	plan->fft2 = STARPUFFT(malloc)(plan->totsize * sizeof(*plan->fft2));	memset(plan->fft2, 0, plan->totsize * sizeof(*plan->fft2));	/* Allocate handle arrays */	plan->twisted1_handle = malloc(plan->totsize1 * sizeof(*plan->twisted1_handle));	plan->fft1_handle = malloc(plan->totsize1 * sizeof(*plan->fft1_handle));	plan->twisted2_handle = malloc(plan->totsize3 * sizeof(*plan->twisted2_handle));	plan->fft2_handle = malloc(plan->totsize3 * sizeof(*plan->fft2_handle));	/* Allocate task arrays */	plan->twist1_tasks = malloc(plan->totsize1 * sizeof(*plan->twist1_tasks));	plan->fft1_tasks = malloc(plan->totsize1 * sizeof(*plan->fft1_tasks));	plan->twist2_tasks = malloc(plan->totsize3 * sizeof(*plan->twist2_tasks));	plan->fft2_tasks = malloc(plan->totsize3 * sizeof(*plan->fft2_tasks));	plan->twist3_tasks = malloc(plan->totsize3 * sizeof(*plan->twist3_tasks));	/* Allocate codelet argument arrays */	plan->fft1_args = malloc(plan->totsize1 * sizeof(*plan->fft1_args));	plan->fft2_args = malloc(plan->totsize3 * sizeof(*plan->fft2_args));	/* Create first-round tasks: DIV_1D tasks of type twist1 and fft1 */	for (z = 0; z < plan->totsize1; z++) {		int i = z;#define STEP_TAG(step)	STEP_TAG_1D(plan, step, i)		/* TODO: get rid of tags */		plan->fft1_args[z].plan = plan;		plan->fft1_args[z].i = i;		/* Register the twisted1 buffer of size n2. */		starpu_vector_data_register(&plan->twisted1_handle[z], STARPU_MAIN_RAM, (uintptr_t) &plan->twisted1[z*plan->totsize2], plan->totsize2, sizeof(*plan->twisted1));		/* Register the fft1 buffer of size n2. */		starpu_vector_data_register(&plan->fft1_handle[z], STARPU_MAIN_RAM, (uintptr_t) &plan->fft1[z*plan->totsize2], plan->totsize2, sizeof(*plan->fft1));		/* We'll need the result of fft1 on the CPU for the second		 * twist anyway, so tell starpu to not keep the fft1 buffer in		 * the GPU. */		starpu_data_set_wt_mask(plan->fft1_handle[z], 1<<0);		/* Create twist1 task */		plan->twist1_tasks[z] = task = starpu_task_create();		task->cl = &STARPUFFT(twist1_1d_codelet);		/* task->handles[0] = to be filled at execution to point		   to the application input. */		task->handles[1] = plan->twisted1_handle[z];		task->cl_arg = &plan->fft1_args[z];		task->tag_id = STEP_TAG(TWIST1);		task->use_tag = 1;		task->destroy = 0;		/* Tell that fft1 depends on twisted1 */		starpu_tag_declare_deps(STEP_TAG(FFT1),				1, STEP_TAG(TWIST1));		/* Create FFT1 task */		plan->fft1_tasks[z] = task = starpu_task_create();		task->cl = &STARPUFFT(fft1_1d_codelet);		task->handles[0] = plan->twisted1_handle[z];		task->handles[1] = plan->fft1_handle[z];		task->handles[2] = plan->roots_handle[0];		task->cl_arg = &plan->fft1_args[z];		task->tag_id = STEP_TAG(FFT1);		task->use_tag = 1;		task->destroy = 0;		/* Tell that the join task will depend on the fft1 task. */		starpu_tag_declare_deps(STEP_TAG_1D(plan, JOIN, 0),				1, STEP_TAG(FFT1));#undef STEP_TAG	}	/* Create the join task, only serving as a dependency point between	 * fft1 and twist2 tasks */	plan->join_task = task = starpu_task_create();	task->cl = NULL;	task->tag_id = STEP_TAG_1D(plan, JOIN, 0);	task->use_tag = 1;	task->destroy = 0;	/* Create second-round tasks: DIV_1D batches of n2/DIV_1D twist2, fft2,	 * and twist3 */	for (z = 0; z < plan->totsize3; z++) {		int jj = z;#define STEP_TAG(step)	STEP_TAG_1D(plan, step, jj)		plan->fft2_args[z].plan = plan;		plan->fft2_args[z].jj = jj;		/* Register n3 twisted2 buffers of size n1 */		starpu_vector_data_register(&plan->twisted2_handle[z], STARPU_MAIN_RAM, (uintptr_t) &plan->twisted2[z*plan->totsize4], plan->totsize4, sizeof(*plan->twisted2));		starpu_vector_data_register(&plan->fft2_handle[z], STARPU_MAIN_RAM, (uintptr_t) &plan->fft2[z*plan->totsize4], plan->totsize4, sizeof(*plan->fft2));		/* We'll need the result of fft2 on the CPU for the third		 * twist anyway, so tell starpu to not keep the fft2 buffer in		 * the GPU. */		starpu_data_set_wt_mask(plan->fft2_handle[z], 1<<0);		/* Tell that twisted2 depends on the join task */		starpu_tag_declare_deps(STEP_TAG(TWIST2),				1, STEP_TAG_1D(plan, JOIN, 0));		/* Create twist2 task */		plan->twist2_tasks[z] = task = starpu_task_create();		task->cl = &STARPUFFT(twist2_1d_codelet);		task->handles[0] = plan->twisted2_handle[z];		task->cl_arg = &plan->fft2_args[z];		task->tag_id = STEP_TAG(TWIST2);		task->use_tag = 1;		task->destroy = 0;		/* Tell that fft2 depends on twisted2 */		starpu_tag_declare_deps(STEP_TAG(FFT2),				1, STEP_TAG(TWIST2));		/* Create FFT2 task */		plan->fft2_tasks[z] = task = starpu_task_create();		task->cl = &STARPUFFT(fft2_1d_codelet);		task->handles[0] = plan->twisted2_handle[z];		task->handles[1] = plan->fft2_handle[z];		task->cl_arg = &plan->fft2_args[z];		task->tag_id = STEP_TAG(FFT2);		task->use_tag = 1;		task->destroy = 0;		/* Tell that twist3 depends on fft2 */		starpu_tag_declare_deps(STEP_TAG(TWIST3),				1, STEP_TAG(FFT2));		/* Create twist3 tasks */		/* These run only on CPUs and thus write directly into the		 * application output buffer. */		plan->twist3_tasks[z] = task = starpu_task_create();		task->cl = &STARPUFFT(twist3_1d_codelet);		task->handles[0] = plan->fft2_handle[z];		task->cl_arg = &plan->fft2_args[z];		task->tag_id = STEP_TAG(TWIST3);		task->use_tag = 1;		task->destroy = 0;		/* Tell that to be completely finished we need to have finished		 * this twisted3 */		starpu_tag_declare_deps(STEP_TAG_1D(plan, END, 0),				1, STEP_TAG(TWIST3));#undef STEP_TAG	}	/* Create end task, only serving as a join point. */	plan->end_task = task = starpu_task_create();	task->cl = NULL;	task->tag_id = STEP_TAG_1D(plan, END, 0);	task->use_tag = 1;	task->destroy = 0;	task->detach = 0;}	return plan;}/* Actually submit all the tasks. */static struct starpu_task *STARPUFFT(start1dC2C)(STARPUFFT(plan) plan, starpu_data_handle_t in, starpu_data_handle_t out){	STARPU_ASSERT(plan->type == C2C);	int z;	int ret;if (PARALLEL) {	for (z=0; z < plan->totsize1; z++) {		ret = starpu_task_submit(plan->twist1_tasks[z]);		if (ret == -ENODEV) return NULL;		STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");		ret = starpu_task_submit(plan->fft1_tasks[z]);		if (ret == -ENODEV) return NULL;		STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");	}	ret = starpu_task_submit(plan->join_task);	if (ret == -ENODEV) return NULL;	STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");	for (z=0; z < plan->totsize3; z++) {		ret = starpu_task_submit(plan->twist2_tasks[z]);		if (ret == -ENODEV) return NULL;		STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");		ret = starpu_task_submit(plan->fft2_tasks[z]);		if (ret == -ENODEV) return NULL;		STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");		ret = starpu_task_submit(plan->twist3_tasks[z]);		if (ret == -ENODEV) return NULL;		STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");	}	ret = starpu_task_submit(plan->end_task);	if (ret == -ENODEV) return NULL;	STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");	return plan->end_task;} else /* !PARALLEL */ {	struct starpu_task *task;	/* Create FFT task */	task = starpu_task_create();	task->detach = 0;	task->cl = &STARPUFFT(fft_1d_codelet);	task->handles[0] = in;	task->handles[1] = out;	task->cl_arg = plan;	ret = starpu_task_submit(task);	if (ret == -ENODEV) return NULL;	STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");	return task;}}/* Free all the tags. The generic code handles freeing the buffers. */static voidSTARPUFFT(free_1d_tags)(STARPUFFT(plan) plan){	unsigned i;	int n1 = plan->n1[0];	if (!PARALLEL)		return;	for (i = 0; i < n1; i++) {		starpu_tag_remove(STEP_TAG_1D(plan, TWIST1, i));		starpu_tag_remove(STEP_TAG_1D(plan, FFT1, i));	}	starpu_tag_remove(STEP_TAG_1D(plan, JOIN, 0));	for (i = 0; i < DIV_1D; i++) {		starpu_tag_remove(STEP_TAG_1D(plan, TWIST2, i));		starpu_tag_remove(STEP_TAG_1D(plan, FFT2, i));		starpu_tag_remove(STEP_TAG_1D(plan, TWIST3, i));	}	starpu_tag_remove(STEP_TAG_1D(plan, END, 0));}
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