amd opencl

String lookup is an important operation in the field of information security and information filtering, especially in real-time processing of large text. As an example, the exact pattern string lookup is performed using GPU OpenCL. 1. Acceleration method (1) Save a small number of constant data, such as pattern string length, text length, and so on, in the private memory of the thread. (2) The mode string is saved in the local memory of the GPU, wh

To summarize, the steps of OpenCL are almost theseFirst to get the platform ID clgetplatformids (nplatforms, platform_id, num_of_platforms)Then get the device ID clgetdeviceids (platform_id[1], CL_DEVICE_TYPE_GPU, 1,%device_id num_of_devices)It is important to note that if there are multiple devices (such as CPUs and GPUs) platform_id must be passed in as an arrayThen there is the creation context Clcreatecontext (properties, 1, device_id, NULL, NULL,

Recently I am looking at opencl programs, but I am not very familiar with the working-item running mechanism. As a result, I took a look at it intuitively with a few small programs, mainly using OpenMP testing ideas to output work-item and the data processing results. I personally think this is very helpful for me to understand its operating mechanism. The following is a program: Host Program: Main. cpp /* Project: multiply the matrix of

In opencl or cuda, the use of volatile is often ignored for access to global shared variables, which will not be problematic only once, however, if the shared variable is accessed for the second time, it will be optimized by the compiler to obtain the value when it is referenced for the first time. That is to say, the current thread will not be visible when other threads modify shared variables. The following is a simple

1. Install NVIDIA graphics driver; then install Opencl/cuda http://blog.csdn.net/canhui_wang/article/details/72540004 2. Configure the local environment for Ethereum Mining sudo apt-gethttps://github.com/genoil/cpp-ethereum/blob/master/readme.md-y install Software-properties-common sudo add-apt-repository-y ppa:ethereum/ethereum sudo apt-get update sudo apt-get install git sudo apt-get install CMake sudo apt-get install Libcryptopp-dev sudo apt-

our primary platforms"Somasegar, vice president of Microsoft Development in the United States, has a high evaluation of AMD's work:"AMD heterogeneous programming is an excellent development tool. Grand Casino and C + + AMP provides valuable development experience and resources to the Linux open source community.Not only that, C + + AMP version 1.2 supports C + + with broad cross-platform compatibility and almost easily supports most platforms:In

our primary platforms"Somasegar, vice president of Microsoft Development in the United States, has a high evaluation of AMD's work:"AMD heterogeneous programming is an excellent development tool. and the C + + AMP provides valuable development experience and resources to the Linux open source community.Not only that, C + + AMP version 1.2 supports C + + with broad cross-platform compatibility and almost easily supports most platforms:In

transferred from: http://hi.baidu.com/fsword73/item/51df1fafe6083e268919d39e Author: fsword73 Bank Conflicts is a common problem in storage access, and avoids bank Conflicts effectively improving storage access speed. The following is a description of two instances, reduction and prefix Sum. 1 use padding in reduction to avoid bank Conflicts AMD HD Readon 5870 For example, the Local Memory has 32Banks, each wavefronts has 64threads, the Bank conflicts

OpenCL copies the array from memory to memory, and openclcopy I wanted to optimize the previous blog, but the optimization effect was not obvious. But remember the knowledge points. The original intention is to move the computing of the defined domain in the previous blog to the CPU for computing. Because the computing of the defined domain is the same for every kernel, direct reading can further reduce the kernel execution time. My idea was to send t

In tutorial 2, we use the converttostring function to read the kernel source file to a string, then use the clcreateprogramwithsource function to load the program object, and then call the clbuildprogram function to compile the program object. In fact, we can also directly call the binary Kernel File, so that when you do not want to show the Kernel File to others, it will play a certain role of confidentiality. In this tutorial, We will store the read source file in a binary file, and create a T

required. We write the results calculated by each working group to the output cache. Because only 8 32-bit data is output, it becomes a piece of cake to take computing in the CPU. The code for the entire project is provided below: OpenCL_Basic.zip (17 K) The above code transmits the calculated results of each Working Group to the host. So can we let the GPU solve these eight results together? The answer is yes. However, here we will use the atomic operation extension in OpenCL1.0. In OpenCL1.1,

How does GPGPU OpenCL implement exact string search? 1. Acceleration Method (1) store a small amount of constant data, such as the mode string length and text length, in the private memory of the thread. (2) Save the mode string in the local memory of the GPU, and accelerate the thread's access to the mode string. (3) Save the text to be searched in global memory, use as many threads as possible to access global memory, and reduce the average thread a

First, install opencv correctly and pass the test.I understand that the GPU environment configuration consists of three main steps.1. Generate the associated file, that is, makefile or project file.2. compile and generate library files related to hardware usage, including dynamic and static library files.3. Add the generated library file to the program. The addition process is similar to that of the opencv library.For more information, see:Http://wenku.baidu.com/link? Url = GGDJLZFwhj26F50GqW-q1

transferred from: http://www.cnblogs.com/mikewolf2002/archive/2012/09/06/2674125.html Author: Mike Old Wolf In tutorial 2, we read the kernel source file into a string string using the function converttostring, and then use the function Clcreateprogramwithsource to load the program object. Call the function Clbuildprogram to compile the program object again. In fact, we can also directly call the binary kernel file, so that when you do not want to kernel file to others to see, play a certain ro

tools and new software platforms to their IT environments. In addition, this demonstration also represents a significant step forward in the x86 APU acceleration performance in the data center. AMD's "Berlin" APU "premiere will show you the world's first heterogeneous system architecture (HSA) using the server APU, which will be officially launched later this year. This demonstration includes an introduction to the advanced results used in "Project Sumatra", which enable Java applications to u

tools and new software platforms to their IT environments. In addition, this demonstration also represents a significant step forward in the x86 APU acceleration performance in the data center. AMD's "Berlin" APU "premiere will show you the world's first heterogeneous system architecture (HSA) using the server APU, which will be officially launched later this year. This demonstration includes an introduction to the advanced achievements used in "Project Sumatra". These advanced achievements mak

Things are still simple, supposedlyPip Install PyopenclBut did not succeed, the error indicates that there is a mako not installed, although said not to install also does not matter, but think of no trouble on the installed, continue to error.Seems to want to install PYOPENCL, you have to install OpenCL, so AMD website OpenCL SDK (2.9.1, version in the table, at

After restructuring, acceleration, and comprehensive transformation, AMD has been reborn. A brand new future-oriented AMD will take into account the traditional PC business and emerging business markets, and face the challenges of the cloud computing era with innovative technology, unique vision and powerful execution. In August 14, the amd chief executive team,

We do high-performance computing friends, presumably to the CPU implementation mode is already very familiar with it. Modern high-level CPUs typically use superscalar pipelining, which enables parallel execution of several mutually independent instructions-called instruction set parallelism (Ilp,instruction-level Parallelism), and SSE (streaming SIMD), like x86 introduced Extension), AVX (Advanced Vector Extension), and arm's neon technology belong to data-level parallelism (Data-level Paralleli

Javasript modularity before understanding the Amd,cmd specification, it is necessary to understand briefly what is modular and modular development? Modularity refers to the systematic decomposition of a problem in order to solve a complex problem or a series of mixed problems, according to a sort of thinking. Modularity is a way of dealing with complex systems that break down into manageable modules that are more logical and maintainable in code struc