merrymercy / tvm-mali Goto Github PK

hi, @merrymercy
I am working on winograd on cuda.
I found that batched MM in your winograd is slow in nvida architecure. I guest this is because when C is large, it could not use parallel power of GPU.

Do you have any idea about this part?

Thanks

I'm running on 32 bits version of Debian Stretch with some issues. What OS image was used for the test?

BR

hi,

This is a great job.

How to save the generated opencl code into a file?

Thanks

hi, @merrymercy

will get_workload load pretrained weights? Where could I find fp16 mobilenet pretrained weight?

Thanks

I import YOLOv2_tiny.onnx from the link below using mali on firefly3399 and got an error on nnvm.compiler.build. It looks like something wrong with conv2d which mail supports. Any idea?

https://github.com/tkat0/chainer-nnvm-example

Traceback (most recent call last):
File "mali_imagenet_bench.py", line 102, in
run_case('tinyYolo2', 'float32')
File "mali_imagenet_bench.py", line 42, in run_case
graph, lib, params = nnvm.compiler.build(net, tvm.target.mali(), shape={input_name: data_shape}, params=params, dtype=dtype, target_host=args.target_host)
File "/usr/local/lib/python2.7/dist-packages/nnvm-0.8.0-py2.7.egg/nnvm/compiler/build_module.py", line 251, in build
graph = graph.apply("GraphFusePartition").apply("GraphFuseCompile")
File "/usr/local/lib/python2.7/dist-packages/nnvm-0.8.0-py2.7.egg/nnvm/graph.py", line 235, in apply
check_call(_LIB.NNGraphApplyPasses(self.handle, npass, cpass, ctypes.byref(ghandle)))
File "/usr/local/lib/python2.7/dist-packages/nnvm-0.8.0-py2.7.egg/nnvm/_base.py", line 72, in check_call
raise NNVMError(py_str(_LIB.NNGetLastError()))
nnvm._base.NNVMError: TVMCall CFunc Error:
Traceback (most recent call last):
File "tvm/_ffi/_cython/function.pxi", line 39, in core.tvm_callback (tvm/_ffi/_cython/core.cpp:3206)
File "/usr/local/lib/python2.7/dist-packages/nnvm-0.8.0-py2.7.egg/nnvm/top/nn.py", line 123, in compute_conv2d
out = topi.nn.conv2d(inputs[0], inputs[1], strides, padding)
File "", line 2, in conv2d
File "/usr/local/lib/python2.7/dist-packages/tvm-0.1.0-py2.7-linux-x86_64.egg/tvm/target.py", line 222, in dispatch_func
return dispatch_dict[k](*args, **kwargs)
File "build/bdist.linux-x86_64/egg/topi/mali/conv2d.py", line 100, in decl_conv2d
return _decl_direct(data, kernel, stride, padding, layout, out_dtype)
File "build/bdist.linux-x86_64/egg/topi/mali/conv2d.py", line 184, in _decl_direct
assert OW % VW == 0, "OW: %d VW : %d" % (OW, VW)
AssertionError: OW: 22 VW : 4

Thanks,

@merrymercy

Is there any tune guide?

Which parameters could be tuned? Why set num_thread = 8?

Thanks

Hi, I saw you do the benchmark test on RK3399. RK3288 has a Mali-T764 GPU. We tried it but the opencl has some problem recognizing the GPU. Do you have idea if TVM supports RK3288?

hi, @merrymercy

in conv2d.py, winograd algorithm do G and B like normal matrix multiplication, this will not reduce multiplication by plus/minus. Is this understood correct?

Thanks