Description
All data types described in Scalar
Data Types and
Vector Data
Types (except bool, half
(unless the cl_khr_fp16
extension is supported), and void) may be also reinterpreted as another
data type of the same size using the as_type() operator for scalar
data types and the as_type operator
for vector data types. When the operand and result type contain the same number of
elements, the bits in the operand shall be returned directly without modification as
the new type. The usual type promotion for function arguments shall not be performed.
n()
For example, as_float(0x3f800000) returns 1.0f, which is
the value that the bit pattern 0x3f800000 has if viewed as an IEEE-754
single precision value.
When the operand and result type contain a different number of elements, the result
shall be implementation-defined except if the operand is a 4-component vector and the
result is a 3-component vector. In this case, the bits in the operand shall be returned
directly without modification as the new type. That is, a conforming implementation shall
explicitly define a behavior, but two conforming implementations need not have the same
behavior when the number of elements in the result and operand types does not match. The
implementation may define the result to contain all, some or none of the original bits
in whatever order it chooses. It is an error to use the as_type()
or as_type operators to reinterpret
data to a type of a different number of bytes.
n()
Notes
While the union is intended to reflect the organization
of data in memory, the as_type() and
as_type constructs are intended
to reflect the organization of data in register. The n()as_type()
and as_type constructs are intended
to compile to no instructions on devices that use a shared register file designed to
operate on both the operand and result types.
n()
Note that while differences in memory organization are expected to largely be limited to those arising from endianness, the register based representation may also differ due to size of the element in register. (For example, an architecture may load a char into a 32-bit register, or a char vector into a SIMD vector register with fixed 32-bit element size.)
If the element count does not match, then the implementation should pick a data
representation that most closely matches what would happen if an appropriate result type
operator was applied to a register containing data of the source type. If the number of
elements matches, then the as_type
should faithfully reproduce the behavior expected from a similar data type
reinterpretation using memory/unions. So, for example if an implementation stores
all single precision data as double in register, it should implement as_int( float )
by first downconverting the double to single precision and then (if necessary) moving
the single precision bits to a register suitable for operating on integer data.
n()
If data stored in different address spaces do not have the same endianness, then the "dominant endianness" of the device should prevail.
Example
| float f = 1.0f; uint u = as_uint(f); // Legal. Contains: 0x3f800000 float4 f = (float4)(1.0f, 2.0f, 3.0f, 4.0f); // Legal. Contains: (int4) // (0x3f800000, 0x40000000, 0x40400000, 0x40800000) int4 i = as_int4(f); float4 f, g; int4 is_less = f < g; // Legal. f[i] = f[i] < g[i] ? f[i] : 0.0f f = as_float4(as_int4(f) & is_less); int i; // Legal. Result is implementation-defined. short2 j = as_short2(i); int4 i; // Legal. Result is implementation-defined. short8 j = as_short8(i); float4 f; //Error. result and operand have different size double4 g = as_double4(f); // Only if double is supported. float4 f; // Legal. g.xyz will have same values as f.xyz. g.w is undefined float3 g = as_float3(f); |
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