My TX1 has a RAM of 4GB and internal memory space remaining 1.5 GB and have used part of sd card for swap memory of 10 GB and allocated swappiness of 100. Still when i run a tensorflow code for object detection using webcam it still shows below
“tensorflow/core/common_runtime/bfc_allocator.cc:239] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.27GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available”
Even when i have allocated 100 swappines when tensorflow is running only swap memory of 1.4 to 1.6 gb is used and Ram memory gets almost full. Any one please help me how to make swap memory utilization higher than RAM and finally to get results for my tensorflow program.