[SYCL][CUDA][DOC] Added Tensor Cores supported param combinations table to joint_matrix extension doc (#9019)

This PR documents the supported joint_matrix API parameters sets when
using `ext_oneapi_cuda`, similar to the XMX, AMX tables added here:
#7964

This will allow us to point people who would like to use `joint_matrix`
on a specific architecture to the extension document. E.g.
#8795

---------

Signed-off-by: JackAKirk <[email protected]>

Author: JackAKirk

sycl/doc/extensions/experimental/sycl_ext_oneapi_matrix/sycl_ext_oneapi_matrix.asciidoc

@@ -579,6 +579,59 @@ for (int i = 0; i < data.length; ++i) {
 }
 ```
 
+=== Appendix: Supported Parameter Combinations Per Hardware
+
+The tables below provide a list of the parameter combinations that
+`joint_matrix` implementations support on each supported vendors hardware type.
+
+==== Nvidia Tensor Cores Supported Combinations
+
+The complete set of matrix data types and shapes that are supported by the `ext_oneapi_cuda` backend are represented in the following table. Tm indicates the matrix element data type held by a "multiplicand" `joint_matrix`: i.e requiring `use::a` or `use::b`. Tc indicates the matrix element data type held by an "accumulator" `joint_matrix`: i.e requiring `use::accumulator`.
+
+IMPORTANT: When compiling for the `ext_oneapi_cuda` backend the target arch backend flag, `-Xsycl-target-backend --cuda-gpu-arch=sm_xx`, must be used, where `sm_xx` must be a Compute Capability that is equal to or greater than the appropriate Minimum Compute Capability. When an executable has been compiled for `sm_xx`, if the executable is run on a device with compute capability less than `sm_xx` then an error will be thrown. The mapping to Minimum Compute Capability from each supported parameter combination is specified in the following table.
+
+--
+[.center]
+|======================
+|Tm (`use::a` or `use::b`) |Tc (`use::accumulator`) |M |N |K | Minimum Compute Capability
+.3+|half  .3+|float
+|16 |16 |16 .6+| sm_70
+|8 |32 |16
+|32 |8 |16
+.3+|half  .3+|half
+|16 |16 |16
+|8 |32 |16
+|32 |8 |16
+.3+|int8_t  .3+|int32_t
+|16 |16 |16 .6+| sm_72
+|8 |32 |16
+|32 |8 |16
+.3+|uint8_t  .3+|int32_t
+|16 |16 |16
+|8 |32 |16
+|32 |8 |16
+|precision::tf32  |float |16 |16 |8 .5+| sm_80
+.3+|bfloat16  .3+|float
+|16 |16 |16
+|8 |32 |16
+|32 |8 |16
+|double  |double |8 |8 |4
+|======================
+--
+
+The M, N, K triple from the above table defines the complete set of matrix shapes constructible:
+--
+[.center]
+|======================
+|use |NumRows | NumCols
+|a |M |K
+|b |K |N
+|accumulator | M| N
+|======================
+--
+
+IMPORTANT: The `stride` argument to `joint_matrix_load` and `joint_matrix_store` must be a multiple of 8 when `T` is `half`, and a multiple of 4 when `T` is `float`; where `T` is the type of the `joint_matrix` elements. When `T` is not `half` or `float` there are no restrictions to `stride`.
+
 ## TODO List
 - Add WI data to joint matrix mapping coordinates information for piece-wise operations. This will be added as part of the query or new methods to the 'get_wi_data' class. 
 - Add a more realistic and complete example that shows the value of the general query.