其中shared_ld_bank_conflict是load bank conflict次数,shared_st_bank_conflict是store bank conflict次数. 可以看出kernel1有992次的store bank conflict,992 = 31*32,正好符合预期. 这里还有一个问题:kernel1最后执行了A[tid] = data[row][col],按道理来说应该也存在load bank conflict.但是为什么使用nvprof显示...
其中shared_ld_bank_conflict是load bank conflict次数,shared_st_bank_conflict是store bank conflict次数. 可以看出kernel1有992次的store bank conflict,992 = 31*32,正好符合预期. 这里还有一个问题:kernel1最后执行了A[tid] = data[row][col],按道理来说应该也存在load bank conflict.但是为什么使用nvprof显示...
避免的bank conflict的一种方法是对shared memory使用padding,通过在尾部padding一个元素,数组变为s_data[32][33],这样相同列的不同行的元素的bank值不再一样,在转置时就避免了bank冲突。如下图所示: 新的代码如下: __global__voidmatrix_trans_shm_padding(int*dev_A,intM,intN,int*dev_B){introw=blockI...
l1tex__data_bank_conflicts_pipe_lsu_mem_shared_op_ld.sum 表示总的 conflict 数量; l1tex__data_pipe_lsu_wavefronts_mem_shared_op_ld.sum 表示总的 shared memory load transaction 的数量; Case 2 这个模式就是符合了合并条件中的第一条。 所以两个 half warp 的访问合并,一共只有 1 次 memory tr...
nvprof ./bankconflict 1. 结果如下: 可以明显看出kernel2的执行速度比kernel1快了很多. 另外,使用nvprof还能分析程序发生bank conflict的次数,执行: nvprof --events shared_ld_bank_conflict,shared_st_bank_conflict ./bankcon 1. 注:docker内执行nvprof --events或者--metrics时,要在启动docker时使用--privileg...
Now a few have suggested this 2 way bank conflict can be avoided, if we pad 64 bit data with 32 more bits. so 64 bits with additional padded 32 bits will be 96 bits(12 bytes) data which will occupy three consecutive banks in shared memory, where each bank width i...
if (continue_condition()) flag[threadIdx.y] = 1; // drawback: possible bank conflict } while (flag[threadIdx.y]); // etc. What I pointed out was that this kind of a loop can become infinite if the volatile keyword is left out. ...
LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47(3):291-295. PubMedGoogle ScholarCrossref 41. Ning Z, Pawitan Y, Shen X. High-definition likelihood inference of genetic correlations across human complex traits...
1. bank conflict的原因以及common解法 2. ldmatrix的工作原理Bank Conflict造成的原因以及common解 快速过一下这个部分,细节可以参考nv的文档,shared memory被分为32bank,每个bank的位宽是4bytes,如果同一个warp中的不同线程访存到同一个bank中,会造成bank conflict,但当GPU每个线程访存大于4bytes即每个warp大于128by...
If you use 32-bit mode as in [1] on a device that supports 64-bit transactions, it says that no bank conflict is created when two 32-bit addresses are accessed in the same 64-bit word as it maps to one memory bank and can be multicasted to the two threads in the same warp. ...