Question

我知道：

https://github.com/lsegal/barracuda

自01/11以来尚未更新

并且

http://rubyforge.org/projects/ruby-opencl/

自03/10以来尚未更新。

这些项目是否已经死亡？或者他们根本没有改变，因为他们的功能，OpenCL / Ruby从那时起没有改变。有人使用这些项目吗？运气好吗？

如果没有，你能为Ruby推荐另一个opencl gem吗？或者这种呼叫通常是如何完成的？只需从Ruby调用raw C？

Answer 1

您可以尝试opencl_ruby_ffi，它是由我的同事积极开发的，并且与OpenCL版本1.2配合得很好。 OpenCL 2.0也应尽快推出。

sudo gem install opencl_ruby_ffi

In Khronos forum您可以找到一个快速示例，说明它的工作原理：

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, [65536],: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!"

Answer 2

您可能希望将您想要的任何C功能打包为gem。这非常简单，这样您就可以将所有c逻辑包装在特定的命名空间中，以便在其他项目中重用。

http://guides.rubygems.org/c-extensions/

Answer 3

如果您想使用GPU进行高速计算，Cumo / NArray是一个不错的选择。 Cumo具有与NArray相同的接口。虽然是cuda而不是opencl。

https://github.com/sonots/cumo

Ruby有一个很好的openCL包装器吗？

3 个答案: