sse2

I need to do determine processor support for SSE2 prior installing a software. From what I understand, I came up with this: bool TestSSE2(char * szErrorMsg) { __try { __asm { xorpd xmm0, xmm0 // executing SSE2 instruction } } #pragma warning (suppress: 6320) __except (EXCEPTION_EXECUTE_HANDLER) { if (_exception_code() == STATUS_ILLEGAL_INSTRUCTION) { _tcscpy_s(szErrorMsg,MSGSIZE, _T("Streaming SIMD Extensions 2(SSE2) is not supported by the CPU.\r\n Unable to launch APP")); return false; } _tcscpy_s(szErrorMsg,MSGSIZE, _T("Streaming SIMD Extensions 2(SSE2) is not supported by the CPU.\r\n

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

I want to use Valgrind 3.7.0 to find memory leaks in my Java native code. I'm using jdk1.6.0._29. To do that, I have to set the --trace-children=yes flag. Setting that flag, I no longer can run valgrind on any java application, even a command like: valgrind --trace-children=yes --smc-check=all java -version will get the error message: Error occurred during initialization of VM Unknown x64 processor: SSE2 not supported I've seen this link: https://bugs.kde.org/show_bug.cgi?id=249943 , but it was not useful. Running the program without Valgrind or without the --trace-children flag is fine. Does

This question already has an answer here: Sum reduction of unsigned bytes without overflow, using SSE2 on Intel 2 answers I am new to SSE2 instructions. I have found an instruction _mm_add_epi8 which can add two array elements. But I want an SSE instruction which can add all elements of an array. I was trying to develop this concept using this code: #include <iostream> #include <conio.h> #include <emmintrin.h> void sse(unsigned char* a,unsigned char* b); void main() { /*unsigned char *arr; arr=(unsigned char *)malloc(50);*/ unsigned char arr[]={'a','b','c','d','e','f','i','j','k','l','m','n',

I should count the number of set bits of a __m128i register. In particular, I should write two functions that are able to count the number of bits of the register, using the following ways. The total number of set bits of the register. The number of set bits for each byte of the register. Are there intrinsic functions that can perform, wholly or partially, the above operations? Here are some codes I used in an old project ( there is a research paper about it ). The function popcnt8 below computes the number of bits set in each byte. SSE2-only version (based on Algorithm 3 in Hacker's Delight

I want to calculate y = ax + b , where x and y is a pixel value [i.e, byte with value range is 0~255], while a and b is a float Since I need to apply this formula for each pixel in image, in addition, a and b is different for different pixel. Direct calculation in C++ is slow, so I am kind of interest to know the sse2 instruction in c++.. After searching, I find that the multiplication and addition in float with sse2 is just as _mm_mul_ps and _mm_add_ps . But in the first place I need to convert the x in byte to float (4 byte). The question is, after I load the data from byte-data source ( _mm

Is there any difference between logical SSE intrinsics for different types? For example if we take OR operation, there are three intrinsics: _mm_or_ps, _mm_or_pd and _mm_or_si128 all of which do the same thing: compute bitwise OR of their operands. My questions: Is there any difference between using one or another intrinsic (with appropriate type casting). Won't there be any hidden costs like longer execution in some specific situation? These intrinsics maps to three different x86 instructions (por, orps, orpd). Does anyone have any ideas why Intel is wasting precious opcode space for several