opencl

FPGA的HLS案例开发｜基于Kintex-7、Zynq-7045_7100开发板

由 橙三吉。 提交于 2021-02-19 20:51:26
FPGA的HLS案例开发｜基于Kintex-7、Zynq-7045_7100开发板 前 言 本文基于创龙科技TLK7-EVM开发板，是一款基于Xilinx Kintex-7系列FPGA设计的高端评估板，由核心板和评估底板组成。核心板经过专业的PCB Layout和高低温测试验证，稳定可靠，可满足各种工业应用环境。 评估板接口资源丰富，引出FMC、SFP+、PCIe、SATA、HDMI等接口，方便用户快速进行产品方案评估与技术预研。 图1 TLK7-EVM评估板 开发案例主要包括： l CameraLink、SDI、HDMI、PAL视频输入/输出案例 l 高速AD(AD9613)采集+高速DA(AD9706)输出案例 l AD9361软件无线电案例 l UDP(10G)光口通信案例 l UDP(1G)光口通信案例 l Aurora光口通信案例 l PCIe通信案例 l 案例源码、产品资料（用户手册、核心板硬件资料、产品规格书）：site.tronlong.com/pfdownload 本文主要介绍HLS案例的使用说明，适用开发环境：Windows 7/10 64bit、Xilinx Vivado 2017.4、Xilinx VivadoHLS 2017.4、Xilinx SDK 2017.4。 Xilinx Vivado HLS（High-Level Synthesis，高层次综合

OpenCL enqueued kernels using lots of host memory

由 ￣綄美尐妖づ 提交于 2021-02-19 08:22:30
问题 I am executing monte carlo sweeps on a population of replicas of my system using OpenCL kernels. After the initial debugging phase I increased some of the arguments to more realistic values and noticed that the program is suddenly eating up large amounts of host memory. I am executing 1000 sweeps on about 4000 replicas, each sweep consists of 2 kernel invocations. That results in about 8 million kernel invocations. The source of the memory usage was easy to find (see screenshot). While the

pyopenCL, openCL, Can't build program on GPU

由 喜你入骨 提交于 2021-02-10 20:21:58
问题 I have a piece of kernel source which runs on the G970 on my PC but won't compile on my early 2015 MacBook pro with Iris 6100 1536MB graphic. platform = cl.get_platforms()[0] device = platform.get_devices()[1] # Get the GPU ID ctx = cl.Context([device]) # Tell CL to use GPU queue = cl.CommandQueue(ctx) # Create a command queue for the target device. # program = cl.Program(ctx, kernelsource).build() print platform.get_devices() This get_devices() show I have 'Intel(R) Core(TM) i5-5287U CPU @ 2

Get OpenCL Kernel-argument information

由 余生长醉 提交于 2021-02-10 16:16:49
问题 I have an OpenCL kernel that gets built at runtime from a PTX-kernel string with clCreateProgramWithBinary , and then built. Now at a later point, I am trying to set the kernel Arguments. I retrieve those arguments in an array of void * , so I do not know the size/type of each individual entry. However, that information is stored in the PTX-kernel string, ie. with: .visible .entry my_kernel( .param .u64 param_1, .param .u32 param_2, .param .f64 param_3 ) I can correctly query the number of

OpenCL Buffer Creation

由 ﹥＞﹥吖頭↗ 提交于 2021-02-10 05:13:35
问题 I am fairly new to OpenCL and though I have understood everything up until now, but I am having trouble understanding how buffer objects work. I haven't understood where a buffer object is stored. In this StackOverflow question it is stated that: If you have one device only , probably (99.99%) is going to be in the device. (In rare cases it may be in the host if the device does not have enough memory for the time being) To me, this means that buffer objects are stored in device memory.

OpenCL Buffer Creation

由 ￣綄美尐妖づ 提交于 2021-02-10 05:13:30
问题 I am fairly new to OpenCL and though I have understood everything up until now, but I am having trouble understanding how buffer objects work. I haven't understood where a buffer object is stored. In this StackOverflow question it is stated that: If you have one device only , probably (99.99%) is going to be in the device. (In rare cases it may be in the host if the device does not have enough memory for the time being) To me, this means that buffer objects are stored in device memory.

Troubles with slow speeds in opencl

由 筅森魡賤 提交于 2021-02-08 15:03:53
问题 I am trying to use opencl for the first time, the goal is to calculate the argmin of each row in an array. Since the operation on each row is independent of the others, I thought this would be easy to put on the graphics card. I seem to get worse performance using this code than when i just run the code on the cpu with an outer forloop, any help would be appreciated. Here is the code: #pragma OPENCL EXTENSION cl_khr_fp64 : enable int argmin(global double *array, int end) { double minimum =

Offline compilation for AMD and NVIDIA OpenCL Kernels without cards installed

由 我的未来我决定 提交于 2021-02-08 09:03:52
问题 I was trying to figure out a way to perform offline compilation of OpenCL kernels without installing Graphics cards. I have installed the SDK's. Does anyone has any experience with compiling OpenCL Kernels without having the graphics cards installed for both any one of them NVIDIA or AMD. I had asked a similar question on AMD forums (http://devgurus.amd.com/message/1284379). NVIDIA forums for long are in accessible so couldn't get any help from there. Thanks 回答1: AMD has an OpenCL extension

OpenCL Intel Iris Integrated Graphics exits with Abort Trap 6: Timeout Issue

由 两盒软妹~` 提交于 2021-02-07 19:19:16
问题 I am attempting to write a program that executes Monte Carlo simulations using OpenCL. I have run into an issue involving exponentials. When the value of the variable steps becomes large, approximately 20000, the calculation of the exponent fails unexpectedly, and the program quits with "Abort Trap: 6". This seems to be a bizarre error given that steps should not affect memory allocation. I have tried setting normal , alpha , and beta to 0 but this does not resolve the problem however

BLAS equivalent of a LAPACK function for GPUs

由 半城伤御伤魂 提交于 2021-02-07 15:17:26
问题 In LAPACK there is this function for diagonalization SUBROUTINE DSPGVX( ITYPE, JOBZ, RANGE, UPLO, N, AP, BP, VL, VU, $ IL, IU, ABSTOL, M, W, Z, LDZ, WORK, IWORK, $ IFAIL, INFO ) * I am looking for its GPU implementation. I am trying to find whether this function has been already implemented in CUDA (or OpenCL), but have only found CULA, which is not open source. Therefore and side CUBLAS exists, I wonder how could I know whether a BLAS or CUBLAS equivalent of this subroutine is available. 回答1
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