Cuda无人模拟-共享内存问题

基于Nvidia GPU计算SDK的示例，我创建了两个内核用于无体仿真。第一个不使用共享内存的内核比第二个使用共享内存的内核快15%。为什么使用共享内存的内核会变慢?

• 8192具尸体,
• 每块线程数= 128，
• 每个网格块= 64。
• 设备:GeForce GTX 560 Ti.

第一内核:

#define N 8192
#define EPS2 0.001f
__device__ float4 vel[N];
__device__ float3 force(float4 bi, float4 bj, float3 ai)
{
     float3 r;
     r.x = bj.x - bi.x;
     r.y = bj.y - bi.y;
     r.z = bj.z - bi.z; 
    float distSqr = r.x * r.x + r.y * r.y + r.z * r.z + EPS2;
    float distSixth = distSqr * distSqr * distSqr;
    float invDistCube = 1.0f/sqrtf(distSixth); 
    float s = bj.w * invDistCube;
    ai.x += r.x * s;  
    ai.y += r.y * s;  
    ai.z += r.z * s; 
    return ai;
}
__global__ void points(float4 *pos, float dt)
{ 
     int k = blockIdx.x * blockDim.x + threadIdx.x;
     if(k >= N) return;
     float4 bi, bj, v;
     float3 ai;
     v = vel[k];
     bi = pos[k];
     ai = make_float3(0,0,0);
     for(int i = 0; i < N; i++)
     {
          bj = pos[i];
          ai = force(bi, bj, ai);
     }
     v.x += ai.x * dt;
     v.y += ai.y * dt;
     v.z += ai.z * dt;
     bi.x += v.x * dt;
     bi.y += v.y * dt;
     bi.z += v.z * dt;
     pos[k]=bi;
     vel[k]=v;
 }

第二个内核:

#define N 8192
#define EPS2 0.001f
#define THREADS_PER_BLOCK 128
__device__ float4 vel[N];
__shared__ float4 shPosition[THREADS_PER_BLOCK];
__device__ float3 force(float4 bi, float4 bj, float3 ai)
{
     float3 r;
     r.x = bj.x - bi.x;
     r.y = bj.y - bi.y;
     r.z = bj.z - bi.z; 
     float distSqr = r.x * r.x + r.y * r.y + r.z * r.z + EPS2;
     float distSixth = distSqr * distSqr * distSqr;
     float invDistCube = 1.0f/sqrtf(distSixth); 
     float s = bj.w * invDistCube;
     ai.x += r.x * s;  
     ai.y += r.y * s;  
     ai.z += r.z * s; 
     return ai;
}
__device__ float3  accumulate_tile(float4 myPosition, float3 accel)  
{  
     int i;  
     for (i = 0; i < THREADS_PER_BLOCK; i++) 
     {  
         accel = force(myPosition, shPosition[i], accel);  
     }  
     return accel;  
}  
__global__ void points(float4 *pos, float dt)
{ 
     int k = blockIdx.x * blockDim.x + threadIdx.x;
     if(k >= N) return;
     float4 bi, v;
     float3 ai;
     v = vel[k];
     bi = pos[k];
     ai = make_float3(0.0f, 0.0f, 0.0f);
     int i,tile;
     for(tile=0; tile < N / THREADS_PER_BLOCK; tile++)
     {
          i = tile *  blockDim.x + threadIdx.x;
          shPosition[threadIdx.x] = pos[i];
          __syncthreads();
          ai = accumulate_tile(bi, ai);
          __syncthreads();
     }
     v.x += ai.x * dt;
     v.y += ai.y * dt;
     v.z += ai.z * dt;
     bi.x += v.x * dt;
     bi.y += v.y * dt;
     bi.z += v.z * dt;
    pos[k]=bi;
    vel[k]=v;
}