Skip to content

P
pytensor
提交 bf9e145a authored 作者: Ian Goodfellow's avatar Ian Goodfellow
浏览文件
操作

renamed mysum to myresult

上级 ac1555c0
隐藏空白字符变更
内嵌 并排
正在显示 包含 41 行增加 和 41 行删除
theano/sandbox/cuda/basic_ops.py
浏览文件 @ bf9e145a
......@@ -825,7 +825,7 @@ class GpuCAReduce(GpuOp):
const int threadCount = blockDim.x * blockDim.y * blockDim.z;
const int threadNum = threadIdx.z * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x;
extern __shared__ float buf[];
float mysum = 0.0f;
float myresult = 0.0f;
if (warpSize != 32)
{
......@@ -842,7 +842,7 @@ class GpuCAReduce(GpuOp):
# But only for power or multiple of 2!
new_version = """
__syncthreads(); // some kernel do multiple reduction.
buf[threadNum] = mysum;
buf[threadNum] = myresult;
__syncthreads();
......@@ -885,7 +885,7 @@ class GpuCAReduce(GpuOp):
""" % locals()
return """
__syncthreads(); // some kernel do multiple reduction.
buf[threadNum] = mysum;
buf[threadNum] = myresult;
__syncthreads();
// rest of function is handled by one warp
......@@ -894,9 +894,9 @@ class GpuCAReduce(GpuOp):
//round up all the partial sums into the first `warpSize` elements
for (int i = threadNum + warpSize; i < threadCount; i += warpSize)
{
mysum += buf[i];
myresult += buf[i];
}
buf[threadNum] = mysum;
buf[threadNum] = myresult;
/*Comment this optimization as it don't work on Fermi GPU.
TODO: find why it don't work or put the GPU compute capability into the version
// no sync because only one warp is running
......@@ -936,7 +936,7 @@ class GpuCAReduce(GpuOp):
self._op_guard()
return """
__syncthreads(); // some kernel do multiple reduction.
buf[threadNum] = mysum;
buf[threadNum] = myresult;
__syncthreads();
// rest of function is handled by one warp
......@@ -945,9 +945,9 @@ class GpuCAReduce(GpuOp):
//round up all the partial sums into the first `nb_reduce` elements
for (int i = threadNum + %(nb_reduce)s; i < threadCount; i += %(nb_reduce)s)
{
mysum += buf[i];
myresult += buf[i];
}
%(z_pos)s = mysum;
%(z_pos)s = myresult;
}
""" % locals()
......@@ -1502,7 +1502,7 @@ class GpuCAReduce(GpuOp):
const int threadCount = blockDim.x;
const int threadNum = threadIdx.x;
extern __shared__ float buf[];
float mysum = 0.0f;
float myresult = 0.0f;
if (warpSize != 32)
{
......@@ -1511,7 +1511,7 @@ class GpuCAReduce(GpuOp):
for (int i0 = threadIdx.x; i0 < d0; i0 += blockDim.x)
{
mysum += A[i0];
myresult += A[i0];
}
%(reducebuf)s
}
......@@ -1530,7 +1530,7 @@ class GpuCAReduce(GpuOp):
const int threadCount = blockDim.x;
const int threadNum = threadIdx.x;
extern __shared__ float buf[];
float mysum = 0.0f;
float myresult = 0.0f;
if (warpSize != 32)
{
......@@ -1540,7 +1540,7 @@ class GpuCAReduce(GpuOp):
for (int i0 = threadIdx.x; i0 < d0; i0 += blockDim.x)
{
float Ai = A[i0 * sA0];
mysum += Ai;
myresult += Ai;
}
%(reducebuf)s
}
......@@ -1560,7 +1560,7 @@ class GpuCAReduce(GpuOp):
const int threadCount = blockDim.x * blockDim.y;
const int threadNum = threadIdx.y*blockDim.x + threadIdx.x;
extern __shared__ float buf[];
float mysum = 0.0f;
float myresult = 0.0f;
if (warpSize != 32)
{
......@@ -1572,7 +1572,7 @@ class GpuCAReduce(GpuOp):
for (int i1 = threadIdx.x; i1 < d1; i1 += blockDim.x)
{
float Ai = A[i0 * sA0 + i1 * sA1];
mysum += Ai;
myresult += Ai;
}
}
%(reducebuf)s
......@@ -1619,12 +1619,12 @@ class GpuCAReduce(GpuOp):
%(decl)s{
%(init)s
for (int i0 = blockIdx.x; i0 < d0; i0 += gridDim.x){
mysum = 0;
myresult = 0;
%(for_i1)s{
%(for_i2)s{
%(for_i3)s{
float Ai = A[i3 * sA3 + i2 * sA2 + i1 * sA1 + i0 * sA0];
mysum += Ai;
myresult += Ai;
}
}
}
......@@ -1638,12 +1638,12 @@ class GpuCAReduce(GpuOp):
%(decl)s{
%(init)s
for (int i0 = blockIdx.x; i0 < d0; i0 += gridDim.x){
mysum = 0;
myresult = 0;
%(for_i1)s{
%(for_i2)s{
%(for_i3)s{
float Ai = A[i3 * sA3 + i2 * sA2 + i1 * sA1 + i0 * sA0];
mysum += Ai;
myresult += Ai;
}
}
}
......@@ -1685,10 +1685,10 @@ class GpuCAReduce(GpuOp):
{
for (int i2 = blockIdx.y; i2 < d2; i2 += gridDim.y)
{
float mysum = 0.0f;
float myresult = 0.0f;
for (int i1 = threadIdx.x; i1 < d1; i1 += blockDim.x)
{
mysum += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
myresult += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
}
%(reducebuf)s
}
......@@ -1711,7 +1711,7 @@ class GpuCAReduce(GpuOp):
{
const int threadCount = blockDim.x;
const int threadNum = threadIdx.x;
float mysum = 0.0f;
float myresult = 0.0f;
if (warpSize != 32)
{
......@@ -1725,12 +1725,12 @@ class GpuCAReduce(GpuOp):
int c = i2_D * 32 + threadIdx.x;
if (c < C)
{
mysum = 0;
myresult = 0;
for (int b = 0; b < B; ++b)
{
mysum += X[a * sX0 + b * sX1 + c * sX2];
myresult += X[a * sX0 + b * sX1 + c * sX2];
}
Z[a * sZ0 + c * sZ1] = mysum;
Z[a * sZ0 + c * sZ1] = myresult;
}
}
}
......@@ -1772,7 +1772,7 @@ class GpuCAReduce(GpuOp):
{
for (int i1 = threadIdx.y; i1 < d1; i1 += blockDim.y)
{
mysum += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
myresult += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
}
%(reducebuf)s
}
......@@ -1800,7 +1800,7 @@ class GpuCAReduce(GpuOp):
const int threadCount = blockDim.x * blockDim.y;
const int threadNum = threadIdx.y * blockDim.x + threadIdx.x;
extern __shared__ float buf[];
float mysum = 0.0f;
float myresult = 0.0f;
if (warpSize != 32)
{
......@@ -1814,7 +1814,7 @@ class GpuCAReduce(GpuOp):
for (int i1 = threadIdx.x; i1 < d1; i1 += blockDim.x)
{
float Ai = A[i0 * sA0 + i1 * sA1 + blockIdx.x * sA2];
mysum += Ai;
myresult += Ai;
}
}
......@@ -1834,10 +1834,10 @@ class GpuCAReduce(GpuOp):
{
for (int i1 = blockIdx.x; i1 < d1; i1 += gridDim.x)
{
mysum = 0;
myresult = 0;
for (int i0 = threadIdx.x; i0 < d0; i0 += blockDim.x)
{
mysum += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
myresult += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
}
%(reducebuf)s
}
......@@ -1853,14 +1853,14 @@ class GpuCAReduce(GpuOp):
%(decl)s
{
%(init)s
mysum = 0;
myresult = 0;
for (int i0 = threadIdx.z; i0 < d0; i0 += blockDim.z)
{
for (int i1 = threadIdx.y; i1 < d1; i1 += blockDim.y)
{
for (int i2 = threadIdx.x; i2 < d2; i2 += blockDim.x)
{
mysum += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
myresult += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
}
}
}
......@@ -1894,10 +1894,10 @@ class GpuCAReduce(GpuOp):
{
for (int i1 = blockIdx.y; i1 < d1; i1 += gridDim.y)
{
float mysum = 0.0f;
float myresult = 0.0f;
for (int i2 = threadIdx.x; i2 < d2; i2 += blockDim.x)
{
mysum += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
myresult += A[i0 * sA0 + i1 * sA1 + i2 * sA2];
}
%(reducebuf)s
}
......@@ -1920,12 +1920,12 @@ class GpuCAReduce(GpuOp):
{
for (int i1 = blockIdx.y; i1 < d1; i1 += gridDim.y)
{
float mysum = 0.0f;
float myresult = 0.0f;
for (int i2 = threadIdx.y; i2 < d2; i2 += blockDim.y)
{
for (int i3 = threadIdx.x; i3 < d3; i3 += blockDim.x)
{
mysum += A[i0 * sA0 + i1 * sA1 + i2 * sA2 + i3 * sA3];
myresult += A[i0 * sA0 + i1 * sA1 + i2 * sA2 + i3 * sA3];
}
}
%(reducebuf)s
......@@ -1949,12 +1949,12 @@ class GpuCAReduce(GpuOp):
{
for (int i2 = blockIdx.y; i2 < d2; i2 += gridDim.y)
{
float mysum = 0.0f;
float myresult = 0.0f;
for (int i1 = threadIdx.y; i1 < d1; i1 += blockDim.y)
{
for (int i3 = threadIdx.x; i3 < d3; i3 += blockDim.x)
{
mysum += A[i0 * sA0 + i1 * sA1 + i2 * sA2 + i3 * sA3];
myresult += A[i0 * sA0 + i1 * sA1 + i2 * sA2 + i3 * sA3];
}
}
%(reducebuf)s
......@@ -1971,7 +1971,7 @@ class GpuCAReduce(GpuOp):
%(decl)s
{
%(init)s
mysum = 0;
myresult = 0;
for (int i0 = 0; i0 < d0; i0++)
for (int i1 = threadIdx.z; i1 < d1; i1 += blockDim.z)
{
......@@ -1979,7 +1979,7 @@ class GpuCAReduce(GpuOp):
{
for (int i3 = threadIdx.x; i3 < d3; i3 += blockDim.x)
{
mysum += A[i0 * sA0 + i1 * sA1 + i2 * sA2 + i3 * sA3];
myresult += A[i0 * sA0 + i1 * sA1 + i2 * sA2 + i3 * sA3];
}
}
}
......@@ -2002,7 +2002,7 @@ class GpuCAReduce(GpuOp):
const int threadCount = blockDim.x * blockDim.y * blockDim.z;
const int threadNum = threadIdx.z * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x;
extern __shared__ float buf[];
float mysum = 0.0f;
float myresult = 0.0f;
if (warpSize != 32)
{
......@@ -2016,7 +2016,7 @@ class GpuCAReduce(GpuOp):
for (int i3 = threadIdx.x; i3 < d3; i3 += blockDim.x)
{
float Ai = A[i0 * sA0 + blockIdx.x * sA1 + i2 * sA2 + i3 * sA3];
mysum += Ai;
myresult += Ai;
}
}
}
......
Markdown 格式
0% 或
您添加了 0 人 到此讨论。请谨慎行事。
请先完成此评论的编辑！
请 注册 或者 后发表评论