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→Byungho's Findings
=== Assignment 1 ===
====Byungho's Findings====
=====Introduction=====
To enhance image quality, most of S/W use convolution algorithm with sharpen kernel. The convolution algorithm is based on matrix matrix multiplication and the kernel which consists of 3 x 3 matrix or 5 x 5 matrix. Therefore, as we learned at the GPU610 class, I can speed up the program using CUDA library
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These two images show the result of the S/W. Left picture is the original image and right picture is obtained from by the S/W. The 3x3 matrix sharpen kernel is 3x3 matrixwas used. =====Analysis===== <code> % cumulative self self total time seconds seconds calls ns/call ns/call name 93.59 1.46 1.46 filter(image_t*, double*, int, double, double) 6.41 1.56 0.10 5038848 19.85 19.85 put_pixel_unsafe(image_t*, unsigned int, unsigned int, unsigned char, unsigned char, unsigned char) 0.00 1.56 0.00 2 0.00 0.00 alloc_img(unsigned int, unsigned int) 0.00 1.56 0.00 1 0.00 0.00 _GLOBAL__sub_I__Z7get_ppmP8_IO_FILE 0.00 1.56 0.00 1 0.00 0.00 get_ppm(_IO_FILE*)</code> <code>image filter(image im, double *K, int Ks, double divisor, double offset){ image oi; unsigned int ix, iy, l; int kx, ky; double cp[3]; oi = alloc_img(im->width, im->height); if ( oi != NULL ) { for(ix=0; ix < im->width; ix++) { for(iy=0; iy < im->height; iy++) { cp[0] = cp[1] = cp[2] = 0.0; for(kx=-Ks; kx <= Ks; kx++) { for(ky=-Ks; ky <= Ks; ky++) { for(l=0; l<3; l++) cp[l] += (K[(kx+Ks) + (ky+Ks)*(2*Ks+1)]/divisor) * ((double)GET_PIXEL_CHECK(im, ix+kx, iy+ky, l)) + offset; } } for(l=0; l<3; l++) cp[l] = (cp[l]>255.0) ? 255.0 : ((cp[l]<0.0) ? 0.0 : cp[l]) ; put_pixel_unsafe(oi, ix, iy, (color_component)cp[1], (color_component)cp[2], (color_component)cp[0]); } } return oi; } return NULL;}</code>
====Taeyang's Findings====
