我知道：
https://github.com/lsegal/barracuda
自 01/11 以来未更新
和
http://rubyforge.org/projects/ruby-opencl/
自 03/10 以来没有更新。
这些项目死了吗？或者它们只是因为它们的功能而没有改变，而 OpenCL/Ruby 从那时起就没有改变。有人在使用这些项目吗？运气好的话？
如果没有，你能推荐另一个用于 Ruby 的 opencl gem 吗？或者这种电话通常是如何完成的？只需从 Ruby 调用原始 C？
您可以尝试opencl_ruby_ffi，它是积极开发的（由我的一位同事）并且与 OpenCL 1.2 版配合得很好。OpenCL 2.0 也应该很快就会推出。
sudo gem install opencl_ruby_ffi
在 Khronos 论坛中，您可以找到一个展示其工作原理的简单示例：
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!"
您可能希望将任何您想要的 C 功能打包为 gem。这非常简单，通过这种方式，您可以将所有 c 逻辑包装在一个特定的命名空间中，您可以在其他项目中重用该命名空间。
如果你想用 GPU 做高速计算，Cumo / NArray 是一个不错的选择。Cumo 具有与 NArray 相同的接口。虽然它是 cuda 而不是 opencl。