sse

I have a short to float cast in C++ that is bottlenecking my code. The code translates from a hardware device buffer which is natively shorts, this represents the input from a fancy photon counter. float factor= 1.0f/value; for (int i = 0; i < W*H; i++)//25% of time is spent doing this { int value = source[i];//ushort -> int destination[i] = value*factor;//int*float->float } A few details Value should go from 0 to 2^16-1, it represents the pixel values of a highly sensitive camera I'm on a multicore x86 machine with an i7 processor (i7 960 which is SSE 4.2 and 4.1). Source is aligned to an 8

Suppose I have an array: uint8_t arr[256]; and an element __m128i x containing 16 bytes, x_1, x_2, ... x_16 I would like to efficiently fill a new __m128i element __m128i y with values from arr depending on the values in x , such that: y_1 = arr[x_1] y_2 = arr[x_2] . . . y_16 = arr[x_16] A command to achieve this would essentially be loading a register from a non-contiguous set of memory locations. I have a painfully vague memory of having seen documentation of such a command, but can't find it now. Does it exist? Thanks in advance for your help. This kind of capability in SIMD architectures

I want to do a reduction on an array using OpenMP and SIMD. I read that a reduction in OpenMP is equivalent to: inline float sum_scalar_openmp2(const float a[], const size_t N) { float sum = 0.0f; #pragma omp parallel { float sum_private = 0.0f; #pragma omp parallel for nowait for(int i=0; i<N; i++) { sum_private += a[i]; } #pragma omp atomic sum += sum_private; } return sum; } I got this idea from the follow link: http://bisqwit.iki.fi/story/howto/openmp/#ReductionClause But atomic also does not support complex operators. What I did was replace atomic with critical and implemented the

This question already has an answer here: Can counting byte matches between two strings be optimized using SIMD? 3 answers I wrote the function int compare_16bytes(__m128i lhs, __m128i rhs) in order to compare two 16 byte numbers using SSE instructions: this function returns how many bytes are equal after performing the comparison. Now I would like use the above function in order to compare two byte arrays of arbitrary length: the length may not be a multiple of 16 bytes, so I need deal with this problem. How could I complete the implementation of the function below? How could I improve the

Looking at the SSE operators CMPORDPS - ordered compare packed singles CMPUNORDPS - unordered compare packed singles What do ordered and unordered mean? I looked for equivalent instructions in the x86 instruction set, and it only seems to have unordered (FUCOM). Mysticial An ordered comparison checks if neither operand is NaN . Conversely, an unordered comparison checks if either operand is a NaN . This page gives some more information on this: http://csapp.cs.cmu.edu/public/waside/waside-sse.pdf (section 5) The idea here is that comparisons with NaN are indeterminate. (can't decide the result

I need to run a matrix-vector multiplication 240000 times per second. The matrix is 5x5 and is always the same, whereas the vector changes at each iteration. The data type is float. I was thinking of using some SSE (or similar) instructions. 1) I am concerned that the number of arithmetic operations is too small compared to the number of memory operations involved. Do you think I can get some tangible (e.g. > 20%) improvement? 2) Do I need the Intel compiler to do it? 3) Can you point out some references? Thanks everybody! The Eigen C++ template library for vectors, matrices, ... has both