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-rwxr-xr-xsrc/Core/performance_CPU/TNV_core.c.v15731
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diff --git a/src/Core/performance_CPU/TNV_core.c.v15 b/src/Core/performance_CPU/TNV_core.c.v15
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+++ b/src/Core/performance_CPU/TNV_core.c.v15
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+/*
+ * This work is part of the Core Imaging Library developed by
+ * Visual Analytics and Imaging System Group of the Science Technology
+ * Facilities Council, STFC
+ *
+ * Copyright 2017 Daniil Kazantsev
+ * Copyright 2017 Srikanth Nagella, Edoardo Pasca
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "TNV_core.h"
+
+#define min(a,b) (((a)<(b))?(a):(b))
+
+/*inline*/ void coefF(float *t, float M1, float M2, float M3, float sigma, int p, int q, int r) {
+ int ii, num;
+ float divsigma = 1.0f / sigma;
+ float sum, shrinkfactor;
+ float T,D,det,eig1,eig2,sig1,sig2,V1, V2, V3, V4, v0,v1,v2, mu1,mu2,sig1_upd,sig2_upd;
+ float proj[2] = {0};
+
+ // Compute eigenvalues of M
+ T = M1 + M3;
+ D = M1 * M3 - M2 * M2;
+ det = sqrtf(MAX((T * T / 4.0f) - D, 0.0f));
+ eig1 = MAX((T / 2.0f) + det, 0.0f);
+ eig2 = MAX((T / 2.0f) - det, 0.0f);
+ sig1 = sqrtf(eig1);
+ sig2 = sqrtf(eig2);
+
+ // Compute normalized eigenvectors
+ V1 = V2 = V3 = V4 = 0.0f;
+
+ if(M2 != 0.0f)
+ {
+ v0 = M2;
+ v1 = eig1 - M3;
+ v2 = eig2 - M3;
+
+ mu1 = sqrtf(v0 * v0 + v1 * v1);
+ mu2 = sqrtf(v0 * v0 + v2 * v2);
+
+ if(mu1 > fTiny)
+ {
+ V1 = v1 / mu1;
+ V3 = v0 / mu1;
+ }
+
+ if(mu2 > fTiny)
+ {
+ V2 = v2 / mu2;
+ V4 = v0 / mu2;
+ }
+
+ } else
+ {
+ if(M1 > M3)
+ {
+ V1 = V4 = 1.0f;
+ V2 = V3 = 0.0f;
+
+ } else
+ {
+ V1 = V4 = 0.0f;
+ V2 = V3 = 1.0f;
+ }
+ }
+
+ // Compute prox_p of the diagonal entries
+ sig1_upd = sig2_upd = 0.0f;
+
+ if(p == 1)
+ {
+ sig1_upd = MAX(sig1 - divsigma, 0.0f);
+ sig2_upd = MAX(sig2 - divsigma, 0.0f);
+
+ } else if(p == INFNORM)
+ {
+ proj[0] = sigma * fabs(sig1);
+ proj[1] = sigma * fabs(sig2);
+
+ /*l1 projection part */
+ sum = fLarge;
+ num = 0l;
+ shrinkfactor = 0.0f;
+ while(sum > 1.0f)
+ {
+ sum = 0.0f;
+ num = 0;
+
+ for(ii = 0; ii < 2; ii++)
+ {
+ proj[ii] = MAX(proj[ii] - shrinkfactor, 0.0f);
+
+ sum += fabs(proj[ii]);
+ if(proj[ii]!= 0.0f)
+ num++;
+ }
+
+ if(num > 0)
+ shrinkfactor = (sum - 1.0f) / num;
+ else
+ break;
+ }
+ /*l1 proj ends*/
+
+ sig1_upd = sig1 - divsigma * proj[0];
+ sig2_upd = sig2 - divsigma * proj[1];
+ }
+
+ // Compute the diagonal entries of $\widehat{\Sigma}\Sigma^{\dagger}_0$
+ if(sig1 > fTiny)
+ sig1_upd /= sig1;
+
+ if(sig2 > fTiny)
+ sig2_upd /= sig2;
+
+ // Compute solution
+ t[0] = sig1_upd * V1 * V1 + sig2_upd * V2 * V2;
+ t[1] = sig1_upd * V1 * V3 + sig2_upd * V2 * V4;
+ t[2] = sig1_upd * V3 * V3 + sig2_upd * V4 * V4;
+}
+
+
+#include "hw_sched.h"
+typedef struct {
+ int offY, stepY, realY, copY;
+ float *Input, *u, *u_upd, *qx, *qy, *qx_upd, *qy_upd, *gradx, *grady, *gradx_upd, *grady_upd;
+ double *div, *div_upd;
+ float resprimal, resdual;
+ float unorm, qnorm, product;
+} tnv_thread_t;
+
+typedef struct {
+ int threads;
+ tnv_thread_t *thr_ctx;
+ float *InputT, *uT;
+ int dimX, dimY, dimZ, padZ;
+ float lambda, sigma, tau, theta;
+} tnv_context_t;
+
+HWSched sched = NULL;
+tnv_context_t tnv_ctx;
+
+
+static int tnv_free(HWThread thr, void *hwctx, int device_id, void *data) {
+ int i,j,k;
+ tnv_context_t *tnv_ctx = (tnv_context_t*)data;
+ tnv_thread_t *ctx = tnv_ctx->thr_ctx + device_id;
+
+ free(ctx->Input);
+ free(ctx->u);
+ free(ctx->u_upd);
+ free(ctx->qx);
+ free(ctx->qy);
+ free(ctx->qx_upd);
+ free(ctx->qy_upd);
+ free(ctx->gradx);
+ free(ctx->grady);
+ free(ctx->gradx_upd);
+ free(ctx->grady_upd);
+ free(ctx->div);
+ free(ctx->div_upd);
+
+ return 0;
+}
+
+static int tnv_init(HWThread thr, void *hwctx, int device_id, void *data) {
+ tnv_context_t *tnv_ctx = (tnv_context_t*)data;
+ tnv_thread_t *ctx = tnv_ctx->thr_ctx + device_id;
+
+ int dimX = tnv_ctx->dimX;
+ int dimY = tnv_ctx->dimY;
+ int dimZ = tnv_ctx->dimZ;
+ int offY = ctx->offY;
+ int stepY = ctx->stepY;
+ int realY = ctx->realY;
+
+// printf("%i %p - %i %i %i x %i %i\n", device_id, ctx, dimX, dimY, dimZ, offY, stepY);
+
+ long DimTotal = (long)(dimX*realY*dimZ);
+ long Dim1Total = (long)(dimX*(stepY+1)*dimZ);
+
+ // Auxiliar vectors
+ ctx->Input = calloc(Dim1Total, sizeof(float));
+ ctx->u = calloc(Dim1Total, sizeof(float));
+ ctx->u_upd = calloc(Dim1Total, sizeof(float));
+ ctx->qx = calloc(DimTotal, sizeof(float));
+ ctx->qy = calloc(DimTotal, sizeof(float));
+ ctx->qx_upd = calloc(DimTotal, sizeof(float));
+ ctx->qy_upd = calloc(DimTotal, sizeof(float));
+ ctx->gradx = calloc(DimTotal, sizeof(float));
+ ctx->grady = calloc(DimTotal, sizeof(float));
+ ctx->gradx_upd = calloc(DimTotal, sizeof(float));
+ ctx->grady_upd = calloc(DimTotal, sizeof(float));
+ ctx->div = calloc(Dim1Total, sizeof(double));
+ ctx->div_upd = calloc(Dim1Total, sizeof(double));
+
+ if ((!ctx->Input)||(!ctx->u)||(!ctx->u_upd)||(!ctx->qx)||(!ctx->qy)||(!ctx->qx_upd)||(!ctx->qy_upd)||(!ctx->gradx)||(!ctx->grady)||(!ctx->gradx_upd)||(!ctx->grady_upd)||(!ctx->div)||(!ctx->div_upd)) {
+ fprintf(stderr, "Error allocating memory\n");
+ exit(-1);
+ }
+
+ return 0;
+}
+
+static int tnv_start(HWThread thr, void *hwctx, int device_id, void *data) {
+ int i,j,k;
+ tnv_context_t *tnv_ctx = (tnv_context_t*)data;
+ tnv_thread_t *ctx = tnv_ctx->thr_ctx + device_id;
+
+ int dimX = tnv_ctx->dimX;
+ int dimY = tnv_ctx->dimY;
+ int dimZ = tnv_ctx->dimZ;
+ int offY = ctx->offY;
+ int stepY = ctx->stepY;
+ int realY = ctx->realY;
+ int copY = ctx->copY;
+
+// printf("%i %p - %i %i %i x %i %i\n", device_id, ctx, dimX, dimY, dimZ, offY, stepY);
+
+ long DimTotal = (long)(dimX*realY*dimZ);
+ long Dim1Total = (long)(dimX*(stepY+1)*dimZ);
+
+ memset(ctx->u, 0, Dim1Total * sizeof(float));
+ memset(ctx->qx, 0, DimTotal * sizeof(float));
+ memset(ctx->qy, 0, DimTotal * sizeof(float));
+ memset(ctx->gradx, 0, DimTotal * sizeof(float));
+ memset(ctx->grady, 0, DimTotal * sizeof(float));
+ memset(ctx->div, 0, Dim1Total * sizeof(double));
+ memset(ctx->u_upd, 0, Dim1Total * sizeof(float));
+ memset(ctx->qx_upd, 0, DimTotal * sizeof(float));
+ memset(ctx->qy_upd, 0, DimTotal * sizeof(float));
+ memset(ctx->gradx_upd, 0, DimTotal * sizeof(float));
+ memset(ctx->grady_upd, 0, DimTotal * sizeof(float));
+ memset(ctx->div_upd, 0, Dim1Total * sizeof(double));
+
+ for(k=0; k<dimZ; k++) {
+ for(j=0; j<copY; j++) {
+ for(i=0; i<dimX; i++) {
+ ctx->Input[j * dimX * dimZ + i * dimZ + k] = tnv_ctx->InputT[k * dimX * dimY + (j + offY) * dimX + i];
+ ctx->u[j * dimX * dimZ + i * dimZ + k] = tnv_ctx->uT[k * dimX * dimY + (j + offY) * dimX + i];
+ }
+ }
+ }
+
+ return 0;
+}
+
+static int tnv_finish(HWThread thr, void *hwctx, int device_id, void *data) {
+ int i,j,k;
+ tnv_context_t *tnv_ctx = (tnv_context_t*)data;
+ tnv_thread_t *ctx = tnv_ctx->thr_ctx + device_id;
+
+ int dimX = tnv_ctx->dimX;
+ int dimY = tnv_ctx->dimY;
+ int dimZ = tnv_ctx->dimZ;
+ int offY = ctx->offY;
+ int stepY = ctx->stepY;
+ int realY = ctx->realY;
+ int copY = ctx->copY;
+
+ long DimTotal = (long)(dimX*realY*dimZ);
+ long Dim1Total = (long)(dimX*(stepY+1)*dimZ);
+
+ for(k=0; k<dimZ; k++) {
+ for(j=0; j<copY; j++) {
+ for(i=0; i<dimX; i++) {
+ tnv_ctx->uT[k * dimX * dimY + (j + offY) * dimX + i] = ctx->u[j * dimX * dimZ + i * dimZ + k];
+ }
+ }
+ }
+
+ return 0;
+}
+
+
+static int tnv_copy(HWThread thr, void *hwctx, int device_id, void *data) {
+ int i,j,k;
+ tnv_context_t *tnv_ctx = (tnv_context_t*)data;
+ tnv_thread_t *ctx = tnv_ctx->thr_ctx + device_id;
+
+ int dimX = tnv_ctx->dimX;
+ int dimY = tnv_ctx->dimY;
+ int dimZ = tnv_ctx->dimZ;
+ int stepY = ctx->stepY;
+ int realY = ctx->realY;
+ long DimTotal = (long)(dimX*realY*dimZ);
+ long Dim1Total = (long)(dimX*(stepY+1)*dimZ);
+
+ // Auxiliar vectors
+ memcpy(ctx->u, ctx->u_upd, Dim1Total * sizeof(float));
+ memcpy(ctx->qx, ctx->qx_upd, DimTotal * sizeof(float));
+ memcpy(ctx->qy, ctx->qy_upd, DimTotal * sizeof(float));
+ memcpy(ctx->gradx, ctx->gradx_upd, DimTotal * sizeof(float));
+ memcpy(ctx->grady, ctx->grady_upd, DimTotal * sizeof(float));
+ memcpy(ctx->div, ctx->div_upd, Dim1Total * sizeof(double));
+
+ return 0;
+}
+
+static int tnv_restore(HWThread thr, void *hwctx, int device_id, void *data) {
+ int i,j,k;
+ tnv_context_t *tnv_ctx = (tnv_context_t*)data;
+ tnv_thread_t *ctx = tnv_ctx->thr_ctx + device_id;
+
+ int dimX = tnv_ctx->dimX;
+ int dimY = tnv_ctx->dimY;
+ int dimZ = tnv_ctx->dimZ;
+ int stepY = ctx->stepY;
+ int realY = ctx->realY;
+ long DimTotal = (long)(dimX*realY*dimZ);
+ long Dim1Total = (long)(dimX*(stepY+1)*dimZ);
+
+ // Auxiliar vectors
+ memcpy(ctx->u_upd, ctx->u, Dim1Total * sizeof(float));
+ memcpy(ctx->qx_upd, ctx->qx, DimTotal * sizeof(float));
+ memcpy(ctx->qy_upd, ctx->qy, DimTotal * sizeof(float));
+ memcpy(ctx->gradx_upd, ctx->gradx, DimTotal * sizeof(float));
+ memcpy(ctx->grady_upd, ctx->grady, DimTotal * sizeof(float));
+ memcpy(ctx->div_upd, ctx->div, Dim1Total * sizeof(double));
+
+ return 0;
+}
+
+
+static int tnv_step(HWThread thr, void *hwctx, int device_id, void *data) {
+ long i, j, k, l, m;
+
+ tnv_context_t *tnv_ctx = (tnv_context_t*)data;
+ tnv_thread_t *ctx = tnv_ctx->thr_ctx + device_id;
+
+ int dimX = tnv_ctx->dimX;
+ int dimY = tnv_ctx->dimY;
+ int dimZ = tnv_ctx->dimZ;
+ int padZ = tnv_ctx->padZ;
+ int offY = ctx->offY;
+ int stepY = ctx->stepY;
+ int copY = ctx->copY;
+
+ float *Input = ctx->Input;
+ float *u = ctx->u;
+ float *u_upd = ctx->u_upd;
+ float *qx = ctx->qx;
+ float *qy = ctx->qy;
+ float *qx_upd = ctx->qx_upd;
+ float *qy_upd = ctx->qy_upd;
+ float *gradx = ctx->gradx;
+ float *grady = ctx->grady;
+ float *gradx_upd = ctx->gradx_upd;
+ float *grady_upd = ctx->grady_upd;
+ double *div = ctx->div;
+ double *div_upd = ctx->div_upd;
+
+ long p = 1l;
+ long q = 1l;
+ long r = 0l;
+
+ float lambda = tnv_ctx->lambda;
+ float sigma = tnv_ctx->sigma;
+ float tau = tnv_ctx->tau;
+ float theta = tnv_ctx->theta;
+
+ float taulambda = tau * lambda;
+ float divtau = 1.0f / tau;
+ float divsigma = 1.0f / sigma;
+ float theta1 = 1.0f + theta;
+ float constant = 1.0f + taulambda;
+
+ float resprimal = 0.0f;
+ float resdual = 0.0f;
+ float product = 0.0f;
+ float unorm = 0.0f;
+ float qnorm = 0.0f;
+
+ float udiff[dimZ];
+ float qxdiff;
+ float qydiff;
+ float divdiff;
+ float gradxdiff[dimZ];
+ float gradydiff[dimZ];
+
+ for(k=0; k < dimZ * dimX; k++) {
+ u_upd[k] = (u[k] + tau * div[k] + taulambda * Input[k])/constant;
+ div_upd[k] = 0;
+ }
+
+ for(j = 0; j < stepY; j++) {
+/* m = j * dimX * dimZ + (dimX - 1) * dimZ;
+ for(k = 0; k < dimZ; k++) {
+ u_upd[k + m] = (u[k + m] + tau * div[k + m] + taulambda * Input[k + m]) / constant;
+ }*/
+
+ for(i=0; i < (dimX /*- 1*/); i++) {
+ l = (j * dimX + i) * dimZ;
+ float t[3];
+ float M1 = 0.0f, M2 = 0.0f, M3 = 0.0f;
+ m = dimX * dimZ;
+
+//#pragma unroll 64
+ for(k = 0; k < dimZ; k++) {
+ u_upd[l + k + m] = (u[l + k + m] + tau * div[l + k + m] + taulambda * Input[l + k + m]) / constant;
+
+ gradx_upd[l + k] = (i == (dimX - 1))?0:(u_upd[l + k + dimZ] - u_upd[l + k]);
+ grady_upd[l + k] = (j == (copY - 1))?0:(u_upd[l + k + dimX * dimZ] - u_upd[l + k]); // We need div from the next thread on last iter
+
+ udiff[k] = u[l + k] - u_upd[l + k];
+ unorm += (udiff[k] * udiff[k]);
+// if ((!k)&&(!i)) printf("%i = %f %f, %f %f\n", offY + j, u[l + k], u_upd[l + k], udiff[k], unorm);
+
+ gradxdiff[k] = gradx[l + k] - gradx_upd[l + k];
+ gradydiff[k] = grady[l + k] - grady_upd[l + k];
+
+ float ubarx = theta1 * gradx_upd[l + k] - theta * gradx[l + k];
+ float ubary = theta1 * grady_upd[l + k] - theta * grady[l + k];
+//#define TNV_NEW_STYLE
+#ifdef TNV_NEW_STYLE
+ qx_upd[l + k] = qx[l + k] + sigma * ubarx;
+ qy_upd[l + k] = qy[l + k] + sigma * ubary;
+
+ float vx = divsigma * qx_upd[l + k]; //+ ubarx
+ float vy = divsigma * qy_upd[l + k]; //+ ubary
+#else
+ float vx = ubarx + divsigma * qx[l + k];
+ float vy = ubary + divsigma * qy[l + k];
+#endif
+
+ M1 += (vx * vx); M2 += (vx * vy); M3 += (vy * vy);
+ }
+
+ coefF(t, M1, M2, M3, sigma, p, q, r);
+
+//#pragma unroll 64
+ for(k = 0; k < dimZ; k++) {
+#ifdef TNV_NEW_STYLE
+ float vx = divsigma * qx_upd[l + k];
+ float vy = divsigma * qy_upd[l + k];
+
+ float gx_upd = vx * t[0] + vy * t[1];
+ float gy_upd = vx * t[1] + vy * t[2];
+
+ qx_upd[l + k] -= sigma * gx_upd;
+ qy_upd[l + k] -= sigma * gy_upd;
+#else
+ float ubarx = theta1 * gradx_upd[l + k] - theta * gradx[l + k];
+ float ubary = theta1 * grady_upd[l + k] - theta * grady[l + k];
+ float vx = ubarx + divsigma * qx[l + k];
+ float vy = ubary + divsigma * qy[l + k];
+
+ float gx_upd = vx * t[0] + vy * t[1];
+ float gy_upd = vx * t[1] + vy * t[2];
+
+ qx_upd[l + k] = qx[l + k] + sigma * (ubarx - gx_upd);
+ qy_upd[l + k] = qy[l + k] + sigma * (ubary - gy_upd);
+#endif
+
+if(i != (dimX-1)) {
+ div_upd[l + k] += qx_upd[l + k];
+ div_upd[l + k + dimZ] -= qx_upd[l + k];
+}
+if(j != (copY-1)) {
+ div_upd[l + k] += qy_upd[l + k];
+ div_upd[l + k + dimX * dimZ] = -qy_upd[l + k]; // We need to update div in the next thread on last iter
+}
+
+ qxdiff = qx[l + k] - qx_upd[l + k];
+ qydiff = qy[l + k] - qy_upd[l + k];
+ qnorm += (qxdiff * qxdiff + qydiff * qydiff);
+
+ resdual += fabs(divsigma * qxdiff - gradxdiff[k]);
+ resdual += fabs(divsigma * qydiff - gradydiff[k]);
+ product += (gradxdiff[k] * qxdiff + gradydiff[k] * qydiff);
+
+ if ((offY == 0)||(j > 0)) {
+ divdiff = div[l + k] - div_upd[l + k]; // Multiple steps... How we compute without history?
+ resprimal += fabs(divtau * udiff[k] + divdiff);
+ }
+ }
+
+ } // i
+ }
+
+
+ ctx->resprimal = resprimal;
+ ctx->resdual = resdual;
+ ctx->product = product;
+ ctx->unorm = unorm;
+ ctx->qnorm = qnorm;
+
+ return 0;
+}
+
+static void TNV_CPU_init(float *InputT, float *uT, int dimX, int dimY, int dimZ) {
+ int i, off, size, err;
+
+ if (sched) return;
+
+ tnv_ctx.dimX = dimX;
+ tnv_ctx.dimY = dimY;
+ tnv_ctx.dimZ = dimZ;
+ tnv_ctx.padZ = 64 * ((dimZ / 64) + ((dimZ % 64)?1:0));
+
+ hw_sched_init();
+
+ int threads = hw_sched_get_cpu_count();
+ if (threads > dimY) threads = dimY/2;
+
+ int step = dimY / threads;
+ int extra = dimY % threads;
+
+ tnv_ctx.threads = threads;
+ tnv_ctx.thr_ctx = (tnv_thread_t*)calloc(threads, sizeof(tnv_thread_t));
+ for (i = 0, off = 0; i < threads; i++, off += size) {
+ tnv_thread_t *ctx = tnv_ctx.thr_ctx + i;
+ size = step + ((i < extra)?1:0);
+
+ ctx->offY = off;
+ ctx->stepY = size;
+ ctx->realY = ctx->stepY;
+
+ if (i == (threads-1)) ctx->copY = ctx->stepY;
+ else ctx->copY = ctx->stepY + 1;
+ }
+
+ sched = hw_sched_create(threads);
+ if (!sched) { fprintf(stderr, "Error creating threads\n"); exit(-1); }
+
+ err = hw_sched_schedule_thread_task(sched, (void*)&tnv_ctx, tnv_init);
+ if (!err) err = hw_sched_wait_task(sched);
+ if (err) { fprintf(stderr, "Error %i scheduling init threads", err); exit(-1); }
+}
+
+
+
+/*
+ * C-OMP implementation of Total Nuclear Variation regularisation model (2D + channels) [1]
+ * The code is modified from the implementation by Joan Duran <joan.duran@uib.es> see
+ * "denoisingPDHG_ipol.cpp" in Joans Collaborative Total Variation package
+ *
+ * Input Parameters:
+ * 1. Noisy volume of 2D + channel dimension, i.e. 3D volume
+ * 2. lambda - regularisation parameter
+ * 3. Number of iterations [OPTIONAL parameter]
+ * 4. eplsilon - tolerance constant [OPTIONAL parameter]
+ * 5. print information: 0 (off) or 1 (on) [OPTIONAL parameter]
+ *
+ * Output:
+ * 1. Filtered/regularized image (u)
+ *
+ * [1]. Duran, J., Moeller, M., Sbert, C. and Cremers, D., 2016. Collaborative total variation: a general framework for vectorial TV models. SIAM Journal on Imaging Sciences, 9(1), pp.116-151.
+ */
+
+float TNV_CPU_main(float *InputT, float *uT, float lambda, int maxIter, float tol, int dimX, int dimY, int dimZ)
+{
+ int err;
+ int iter;
+ int i,j,k,l;
+
+ lambda = 1.0f/(2.0f*lambda);
+ tnv_ctx.lambda = lambda;
+
+ // PDHG algorithm parameters
+ float tau = 0.5f;
+ float sigma = 0.5f;
+ float theta = 1.0f;
+
+ // Backtracking parameters
+ float s = 1.0f;
+ float gamma = 0.75f;
+ float beta = 0.95f;
+ float alpha0 = 0.2f;
+ float alpha = alpha0;
+ float delta = 1.5f;
+ float eta = 0.95f;
+
+ TNV_CPU_init(InputT, uT, dimX, dimY, dimZ);
+
+ tnv_ctx.InputT = InputT;
+ tnv_ctx.uT = uT;
+
+ err = hw_sched_schedule_thread_task(sched, (void*)&tnv_ctx, tnv_start);
+ if (!err) err = hw_sched_wait_task(sched);
+ if (err) { fprintf(stderr, "Error %i scheduling start threads", err); exit(-1); }
+
+
+ // Apply Primal-Dual Hybrid Gradient scheme
+ float residual = fLarge;
+ for(iter = 0; iter < maxIter; iter++) {
+ float resprimal = 0.0f;
+ float resdual = 0.0f;
+ float product = 0.0f;
+ float unorm = 0.0f;
+ float qnorm = 0.0f;
+
+ float divtau = 1.0f / tau;
+
+ tnv_ctx.sigma = sigma;
+ tnv_ctx.tau = tau;
+ tnv_ctx.theta = theta;
+
+ err = hw_sched_schedule_thread_task(sched, (void*)&tnv_ctx, tnv_step);
+ if (!err) err = hw_sched_wait_task(sched);
+ if (err) { fprintf(stderr, "Error %i scheduling tnv threads", err); exit(-1); }
+
+ // border regions
+ for (i = 1; i < tnv_ctx.threads; i++) {
+ tnv_thread_t *ctx0 = tnv_ctx.thr_ctx + (i - 1);
+ tnv_thread_t *ctx = tnv_ctx.thr_ctx + i;
+
+ l = ctx0->stepY * dimX * dimZ;
+ for(k=0; k < dimZ * (dimX /*- 1*/); k++) {
+ double div_upd_add = ctx0->div_upd[l + k];
+ ctx->div_upd[k] += div_upd_add;
+ ctx0->div_upd[l + k] = ctx->div_upd[k];
+
+// ctx0->u_upd[l + k] = ctx->u_upd[k];
+
+ float divdiff = ctx->div[k] - ctx->div_upd[k]; // Multiple steps... How we compute without history?
+ float udiff = ctx->u[k] - ctx->u_upd[k];
+ resprimal += fabs(divtau * udiff + divdiff);
+ }
+ }
+
+#define TNV_CHECK_RES
+#ifndef TNV_CHECK_RES
+ for (i = 0; i < tnv_ctx.threads; i++) {
+ tnv_thread_t *ctx = tnv_ctx.thr_ctx + i;
+ resprimal += ctx->resprimal;
+ resdual += ctx->resdual;
+ product += ctx->product;
+ unorm += ctx->unorm;
+ qnorm += ctx->qnorm;
+ }
+#else
+ resprimal = 0;
+ float divsigma = 1.0f / sigma;
+ for(j=0; j<dimY; j++)
+ for(i=0; i<dimX; i++)
+ for(int l=0; l<dimZ; l++)
+ {
+ int step = dimY / tnv_ctx.threads;
+ int extra = dimY % tnv_ctx.threads;
+
+ int thr, subj = j;
+ for (thr = 0; thr < tnv_ctx.threads; thr++) {
+ int size = step;
+ if (thr < extra) size++;
+
+ if (subj >= size) subj-= size;
+ else break;
+ }
+
+ tnv_thread_t *ctx = tnv_ctx.thr_ctx + thr;
+
+ int k = subj * dimX * dimZ + i * dimZ + l;
+
+ float udiff = ctx->u[k] - ctx->u_upd[k];
+ float qxdiff = ctx->qx[k] - ctx->qx_upd[k];
+ float qydiff = ctx->qy[k] - ctx->qy_upd[k];
+ float divdiff = ctx->div[k] - ctx->div_upd[k];
+ float gradxdiff = ctx->gradx[k] - ctx->gradx_upd[k];
+ float gradydiff = ctx->grady[k] - ctx->grady_upd[k];
+
+ resprimal += fabs(divtau*udiff + divdiff);
+ resdual += fabs(divsigma*qxdiff - gradxdiff);
+ resdual += fabs(divsigma*qydiff - gradydiff);
+
+ unorm += (udiff * udiff);
+ qnorm += (qxdiff * qxdiff + qydiff * qydiff);
+ product += (gradxdiff * qxdiff + gradydiff * qydiff);
+ }
+#endif
+
+
+
+ residual = (resprimal + resdual) / ((float) (dimX*dimY*dimZ));
+ float b = (2.0f * tau * sigma * product) / (gamma * sigma * unorm + gamma * tau * qnorm);
+ float dual_dot_delta = resdual * s * delta;
+ float dual_div_delta = (resdual * s) / delta;
+ printf("resprimal: %f, resdual: %f, b: %f (product: %f, unorm: %f, qnorm: %f)\n", resprimal, resdual, b, product, unorm, qnorm);
+
+
+ if(b > 1) {
+ // Decrease step-sizes to fit balancing principle
+ tau = (beta * tau) / b;
+ sigma = (beta * sigma) / b;
+ alpha = alpha0;
+
+ err = hw_sched_schedule_thread_task(sched, (void*)&tnv_ctx, tnv_restore);
+ if (!err) err = hw_sched_wait_task(sched);
+ if (err) { fprintf(stderr, "Error %i scheduling restore threads", err); exit(-1); }
+ } else {
+ err = hw_sched_schedule_thread_task(sched, (void*)&tnv_ctx, tnv_copy);
+ if (!err) err = hw_sched_wait_task(sched);
+ if (err) { fprintf(stderr, "Error %i scheduling copy threads", err); exit(-1); }
+
+ if(resprimal > dual_dot_delta) {
+ // Increase primal step-size and decrease dual step-size
+ tau = tau / (1.0f - alpha);
+ sigma = sigma * (1.0f - alpha);
+ alpha = alpha * eta;
+ } else if(resprimal < dual_div_delta) {
+ // Decrease primal step-size and increase dual step-size
+ tau = tau * (1.0f - alpha);
+ sigma = sigma / (1.0f - alpha);
+ alpha = alpha * eta;
+ }
+ }
+
+ if (residual < tol) break;
+ }
+
+ err = hw_sched_schedule_thread_task(sched, (void*)&tnv_ctx, tnv_finish);
+ if (!err) err = hw_sched_wait_task(sched);
+ if (err) { fprintf(stderr, "Error %i scheduling finish threads", err); exit(-1); }
+
+
+ printf("Iterations stopped at %i with the residual %f \n", iter, residual);
+ printf("Return: %f\n", *uT);
+
+ return *uT;
+}
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