Global load transaction count when in coalesced memory access

I’ve created a simple kernel to test the coalesced memory access by observing the transaction counts, in nvidia gtx980 card. The kernel is,

void copy_coalesced(float * d_in, float * d_out)
    int tid = threadIdx.x + blockIdx.x*blockDim.x;

    d_out[tid] = d_in[tid];

When I run this with the following kernel configurations

#define BLOCKSIZE 32   

int data_size  = 10240;                  //always a multiply of the BLOCKSIZE
int gridSize   = data_size / BLOCKSIZE;

copy_coalesced<<<gridSize, BLOCKSIZE>>>(d_in, d_out);

Since the the data access in the kernel is fully coalasced, and since the data type is float (4 bytes), The number of Load/Store Transactions expected can be found as following,

Load Transaction Size = 32 bytes

Number of floats that can be loaded per transaction = 32 bytes / 4 bytes = 8

Number of transactions needed to load 10240 of data = 10240/8 = 1280 transactions

The same amount of transactions are expected for writing the data as well.

But when observing the nvprof metrics, following was the results

gld_transactions    2560
gst_transactions    1280

gld_transactions_per_request    8.0
gst_transactions_per_request    4.0

I cannot figure out why it takes twice the transactions that it needs for loading the data. But when it comes to load/store efficiency both the metrics gives out 100%

What am I missing out here

Hello BAdhi,

I’ll have a check next week.

Hello BAdhi,

I understand your concern, I also think gld_transactions should be 1280, I’ll raise a bug to dev and let them have a check. Could you tell me which toolkit you use, 7.5 or 8.0?

Best Regards

Hello Harryz,
I am running the same workload on Geforce Titan X and I am facing the same issue on Cuda 8.
Do you know if Nvidia has fixed this bug?