* Improve topk performance.

give 200000 data to compute topk,
before opt: cost 1s
after opt: cost 0.0028s.

* Refine return value.
* Add cuda util funtions.
* Fix ComputeBlockSize bug & refine comments.
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

cudaStreamSynchronize randomly hang when used in multi-thread environment, replace it with cudaStreamQuery API on windows

* refine reallocate of workspace size, test=develop

* add lock to cudnn handle calls, test=develop

TemporaryAllocator is a singleton used for allocating memory for Cudnn. Since it is a singleton, we can delete it for better performance in memory.

We replace TemporaryAllocator by CUDADeviceContextAllocator and CUDADeviceContextAllocation, which uses stream callback to delete the memory allocated for the stream to avoid singleton.

Also added data_feed_proto to operator to fix CI in CPU compilation

Polish fleet API to support cuda collective mode and nccl2 mode

* add config.SetMkldnnCacheCapacity api for mkldnn cache clear strategy

test=develop

* enhance MkldnnPostReset

test=develop

* add comments for mkldnn_cache_capacity field

test=develop

* add mkldnn shapeblob cache clear strategy

test=develop

* refine with comments

test=develop

* make cache clear strategy more safey

test=develop

* add lock for GetShapeBlobSize

test=develop

test=develop

* rename mkldnn set/get_cur_thread_id() to set/get_cur_mkldnn_session_id()

test=develop

* update session id definition and adjust logic for default behavior

test=develop

* reset logic in mkldnn reuse as most of cases work in default.

test=develop

test=develop

* remove nccl dep when the number of GPU is 1
test=develop

* remove attribute in Allocator::Allocate, test=develop

* fix travis ci error, test=develop

* fix cuda/cudnn version detection error, test=develop

* fix again, test=develop

test=develop

test=develop

test=develop

* Support Sync Batch Norm.
* Note, do not enable it in one device.

Usage:

build_strategy = fluid.BuildStrategy()
build_strategy.sync_batch_norm = True
binary = fluid.compiler.CompiledProgram(tp).with_data_parallel(
        loss_name=loss_mean.name,
        build_strategy=build_strategy)

reason: dereferencing smart pointer is the same as the underlying pointer
test=develop

test=develop

test=develop

test=develop
This reverts commit 064512aa.

* remove workspace_handle in conv2d_cudnn
test=develop

* remove workspace_handle
test=develop

* fix bug
test=develop

* make test_conv2d_op SERIAL
test=develop

* save memory in conv_cudnn
test=develop

* enhance thread safety
test=develop

* enhance temporary allocator
test=develop

* Add excess fraction
test=develop

* follow comments
test=develop

* fix bug and code refine
test=develop

* fix memory size check
test=develop

* rename reuse_tmp_allocation_excess_fraction
test=develop

test=develop

test=develop

test=develop

test=develop

* refine tensor
test=develop

* refine tensor
test=develop

* fix device_context log
test=develop

* Add Temporal Allocator

* add Temporay Allocator to DeviceContext
test=develop

* code refine
test=develop

* fix mean_iou
test=develop

* Add DeviceTemporaryAllocator
test=develop

* fix conv_op bug
test=develop

* small fix
test=develop

* code refine
test=develop

* log refine
test=develop

* fix unit test
test=develop

* move double check

* refine concat_and_split
test=develop

* add limit_of_temporary_allocation
test=develop

* fix name
test=develop

test=develop

test=develop

test=develop

* exhaustive search for cuDNN conv.
* Refine code and add unit testing.
* Fix model load in fluid/inference and unit testing in conv2d
* Follow comments.
* Fix compiling test=develop