Consider the following kernel:
__constant float4 oneVec = (float4)(1.0f, 1.0f, 1.0f, 1.0f); __kernel __attribute__((vec_type_hint(float4))) void inverter2(__global float4* input, __global float4* output) { int tid = get_global_id(0); output[tid] = oneVec – input[tid]; output[tid].w = input[tid].w; output[tid] = sqrt(output[tid]); }
For this example of the explicit vector code, the extraction of the
w
component is very costly. The reason is that the next vector
operation forces reloading the same vector from memory. Consider loading
a vector once and performing all changes by use of vector operations even
for a single component.
In this specific case, two changes are required:
oneVec
, so that its w
component
is zero
, causing only a sign flip in the w
component of the input vector.float
representation to manually flip the sign
bit of the w
component back.As a result, the kernel appears as follows:
__constant float4 oneVec = (float4)(1.0f, 1.0f, 1.0f, 0.0f); __constant int4 signChanger = (int4)(0, 0, 0, 0x80000000); __kernel __attribute__((vec_type_hint(float4))) void inverter3(__global float4* input, __global float4* output) { int tid = get_global_id(0); output[tid] = oneVec – input[tid]; output[tid] = as_float4(as_int4(output[tid]) ^ signChanger); output[tid] = sqrt(output[tid]); }
At the cost of another constant vector, this implementation performs
all the required operations addressing only full vectors. All the computations
might also be performed in float8
.