Check failed: error == cudaSuccess (77 vs. 0) an illegal memory access was encountered

[rashmendis]

I'm trying Textboxes++ When I'm looping multiple images, after 6 iterations below error will occur, most people said to downgrade cuDNN to v4 but it is not compatible with Cuda8 and Textboxes++ not compatible below Cuda8. What could be the issue? Please help!

Cuda 8.0 with cuDNN 5.1

I0411 18:45:49.181143 12363 net.cpp:228] pool1 does not need backward computation.
I0411 18:45:49.181152 12363 net.cpp:228] relu1_2 does not need backward computation.
I0411 18:45:49.181162 12363 net.cpp:228] conv1_2 does not need backward computation.
I0411 18:45:49.181172 12363 net.cpp:228] relu1_1 does not need backward computation.
I0411 18:45:49.181181 12363 net.cpp:228] conv1_1 does not need backward computation.
I0411 18:45:49.181193 12363 net.cpp:228] data_input_0_split does not need backward computation.
I0411 18:45:49.181202 12363 net.cpp:228] input does not need backward computation.
I0411 18:45:49.181210 12363 net.cpp:270] This network produces output detection_out
I0411 18:45:49.181360 12363 net.cpp:283] Network initialization done.
I0411 18:45:49.425683 12363 net.cpp:761] Ignoring source layer data
I0411 18:45:49.425726 12363 net.cpp:761] Ignoring source layer data_data_0_split
I0411 18:45:49.455093 12363 net.cpp:761] Ignoring source layer mbox_loss
F0411 18:45:51.959846 12363 math_functions.cu:79] Check failed: error == cudaSuccess (77 vs. 0) an illegal memory access was encountered
*** Check failure stack trace: ***
Aborted (core dumped)

Configuration: Intel i5, 8GB Ram, GeForce GT 740M, Ubuntu 14.04

[Noiredd]

Please read the checklist in the issue template and complete your issue accordingly:

read the guidelines and remove the first paragraph
write a short summary and detailed steps to reproduce
explain how solutions to related problems failed (tick if found none)
fill system configuration
attach relevant logs/config files (tick if not applicable)

In particular, check other solutions - this error has been reported several times, usually being resolved as the GPU's fault, not Caffe's. Also, if you're using some Caffe-based framework, please try to run the same network in vanilla Caffe to make sure this is not a problem with the derived tool but Caffe itself.

[Noiredd]

Closing due to lack of updates. Feel free to reopen when you complete the details requested in the previous post.