我知道:
https://github.com/lsegal/barracuda
自01/11以来尚未更新
和
http://rubyforge.org/projects/ruby-opencl/
自03/10以来尚未更新.
这些项目是否死亡?或者他们根本没有改变,因为它们的功能,OpenCL / Ruby从那以后没有改变.有人使用这些项目吗?运气好的话?
如果没有,你能否推荐另一个用于Ruby的opencl宝石?或者这样的通话是如何进行的?只需从Ruby调用raw C?
谢谢!
解决方法
你可以试试
opencl_ruby_ffi,它是积极开发的(由我的一个同事),并且与OpenCL 1.2版一起工作. OpenCL 2.0也应该即将推出.
- sudo gem install opencl_ruby_ffi
In Khronos forum你可以找到一个快速的例子来显示它的工作原理:
- require 'opencl_ruby_ffi'
- # select the first platform/device available
- # improve it if you have multiple GPU on your machine
- platform = OpenCL::platforms.first
- device = platform.devices.first
- # prepare the source of GPU kernel
- # this is not Ruby but OpenCL C
- source = <<EOF
- __kernel void addition( float2 alpha,__global const float *x,__global float *y) {\n\
- size_t ig = get_global_id(0);\n\
- y[ig] = (alpha.s0 + alpha.s1 + x[ig])*0.3333333333333333333f;\n\
- }
- EOF
- # configure OpenCL environment,refer to OCL API if necessary
- context = OpenCL::create_context(device)
- queue = context.create_command_queue(device,:properties => OpenCL::CommandQueue::PROFILING_ENABLE)
- # create and compile the OpenCL C source code
- prog = context.create_program_with_source(source)
- prog.build
- # allocate cpu (=RAM) buffers and
- # fill the input one with random values
- a_in = NArray.sfloat(65536).random(1.0)
- a_out = NArray.sfloat(65536)
- # allocate GPU buffers matching the cpu ones
- b_in = context.create_buffer(a_in.size * a_in.element_size,:flags => OpenCL::Mem::COPY_HOST_PTR,:host_ptr => a_in)
- b_out = context.create_buffer(a_out.size * a_out.element_size)
- # create a constant pair of float
- f = OpenCL::Float2::new(3.0,2.0)
- # trigger the execution of kernel 'addition' on 128 cores
- event = prog.addition(queue,[65536],f,b_in,b_out,:local_work_size => [128])
- # #Or if you want to be more OpenCL like:
- # k = prog.create_kernel("addition")
- # k.set_arg(0,f)
- # k.set_arg(1,b_in)
- # k.set_arg(2,b_out)
- # event = queue.enqueue_NDrange_kernel(k,:local_work_size => [128])
- # tell OCL to transfer the content GPU buffer b_out
- # to the cpu memory (a_out),but only after `event` (= kernel execution)
- # has completed
- queue.enqueue_read_buffer(b_out,a_out,:event_wait_list => [event])
- # wait for everything in the command queue to finish
- queue.finish
- # now a_out contains the result of the addition performed on the GPU
- # add some cleanup here ...
- # verify that the computation went well
- diff = (a_in - a_out*3.0)
- 65536.times { |i|
- raise "Computation error #{i} : #{diff[i]+f.s0+f.s1}" if (diff[i]+f.s0+f.s1).abs > 0.00001
- }
- puts "Success!"