Add compile-time dispatching examples for generic BLAS and portFFT backends

examples/README.md

@@ -8,6 +8,12 @@ oneMath offers examples with the following routines:
 
 Each routine has one run-time dispatching example and one compile-time dispatching example (which uses both mklcpu and cuda backends), located in `example/<$domain>/run_time_dispatching` and `example/<$domain>/compile_time_dispatching` subfolders, respectively.
 
+In addition, the SYCL-only backends provide standalone compile-time dispatching examples that run on a single SYCL device:
+- blas: `level3/gemm_usm_generic` (built when `ENABLE_GENERIC_BLAS_BACKEND` is enabled)
+- dft: `complex_fwd_usm_portfft` (built when `ENABLE_PORTFFT_BACKEND` is enabled)
+
+These are useful for validating the generic BLAS and portFFT backends, which cannot be combined with any other backend.
+
 To build examples, use cmake build option `-DBUILD_EXAMPLES=true`.
 Compile_time_dispatching will be built if `-DBUILD_EXAMPLES=true` and cuda backend is enabled, because the compile-time dispatching example runs on both mklcpu and cuda backends.
 Run_time_dispatching will be built if `-DBUILD_EXAMPLES=true` and `-DBUILD_SHARED_LIBS=true`.
@@ -180,6 +186,57 @@ Running with single precision real data type on:
 
 BLAS GEMM USM example ran OK on MKLCPU and CUBLAS
 
+```
+
+Compile-time dispatching example with the SYCL-only generic BLAS backend
+```
+$ ./bin/example_blas_gemm_usm_generic
+
+########################################################################
+# General Matrix-Matrix Multiplication using Unified Shared Memory Example:
+#
+# C = alpha * A * B + beta * C
+#
+# where A, B and C are general dense matrices and alpha, beta are
+# floating point type precision scalars.
+#
+# Using apis:
+#   gemm
+#
+# Using single precision (float) data type
+#
+# Running on a SYCL device with the generic BLAS backend
+#
+########################################################################
+
+Running BLAS GEMM USM example on GPU device.
+Device name is: Intel(R) Arc(TM) B580 Graphics
+Running with single precision real data type:
+
+                GEMM parameters:
+                        transA = trans, transB = nontrans
+                        m = 45, n = 98, k = 67
+                        lda = 103, ldB = 105, ldC = 106
+                        alpha = 2, beta = 3
+
+                Outputting 2x2 block of A,B,C matrices:
+
+                        A = [ 0.340188, 0.260249, ...
+                            [ -0.105617, 0.0125354, ...
+                            [ ...
+
+
+                        B = [ -0.326421, -0.192968, ...
+                            [ 0.363891, 0.251295, ...
+                            [ ...
+
+
+                        C = [ 0.00698781, 0.525862, ...
+                            [ 0.585167, 1.59017, ...
+                            [ ...
+
+BLAS GEMM USM example ran OK on the generic backend
+
 ```
 
 ## lapack 
@@ -480,6 +537,33 @@ Unsupported Configuration:
 	oneMath: dft/backends/portfft/commit: function is not implemented REAL domain is unsupported
 ```
 
+Compile-time dispatching example with the SYCL-only portFFT backend
+
+(Note that the portFFT backend only supports the COMPLEX domain.)
+
+```none
+$ ./bin/example_dft_complex_fwd_usm_portfft
+
+########################################################################
+# Complex in-place forward transform for USM API's example:
+#
+# Using APIs:
+#   Compile-time dispatch API
+#   USM forward complex in-place
+#
+# Using single precision (float) data type
+#
+# Running on a SYCL device with the portFFT backend.
+#
+########################################################################
+
+Running DFT complex forward example on GPU device
+Device name is: Intel(R) Arc(TM) B580 Graphics
+Using compile-time dispatch API with portFFT.
+Running with single precision real data type:
+DFT Complex USM example ran OK on portFFT
+```
+
 ## sparse_blas
 
 Run-time dispatching examples with mklcpu backend

examples/blas/compile_time_dispatching/level3/CMakeLists.txt

@@ -17,31 +17,54 @@
 # SPDX-License-Identifier: Apache-2.0
 #===============================================================================
 
-# The example is written for the MKLCPU and CUBLAS backends
-if(NOT (ENABLE_MKLCPU_BACKEND AND ENABLE_CUBLAS_BACKEND))
-  return()
+# The MKLCPU + CUBLAS example is written for the MKLCPU and CUBLAS backends
+if(ENABLE_MKLCPU_BACKEND AND ENABLE_CUBLAS_BACKEND)
+  set(EXAMPLE_TARGET example_blas_gemm_usm_mklcpu_cublas)
+
+  # External applications should use find_package or FetchContent to include oneMath first.
+  # See https://github.com/uxlfoundation/oneMath/blob/develop/docs/using_onemath_with_cmake.rst
+
+  # Create a CMake target with one source file
+  add_executable(${EXAMPLE_TARGET} gemm_usm_mklcpu_cublas.cpp)
+
+  # Linking against onemath_blas_mklcpu and onemath_blas_cublas in CMake will add the required include directories and dependencies.
+  # One can also link against `onemath_blas` to link against all the blas backends built.
+  # These targets should only be used for compile-time dispatching.
+  target_link_libraries(${EXAMPLE_TARGET} PUBLIC
+    onemath_blas_mklcpu
+    onemath_blas_cublas
+  )
+
+  # Include directories specific to the examples
+  target_include_directories(${EXAMPLE_TARGET} PUBLIC
+    ${PROJECT_SOURCE_DIR}/examples/include
+  )
+
+  # Register example as ctest
+  add_test(NAME blas/EXAMPLE/CT/gemm_usm_mklcpu_cublas COMMAND ${EXAMPLE_TARGET})
 endif()
 
-set(EXAMPLE_TARGET example_blas_gemm_usm_mklcpu_cublas)
+# The generic example is written for the SYCL-only generic BLAS backend
+if(ENABLE_GENERIC_BLAS_BACKEND)
+  set(EXAMPLE_TARGET example_blas_gemm_usm_generic)
 
-# External applications should use find_package or FetchContent to include oneMath first.
-# See https://github.com/uxlfoundation/oneMath/blob/develop/docs/using_onemath_with_cmake.rst
+  # External applications should use find_package or FetchContent to include oneMath first.
+  # See https://github.com/uxlfoundation/oneMath/blob/develop/docs/using_onemath_with_cmake.rst
 
-# Create a CMake target with one source file
-add_executable(${EXAMPLE_TARGET} gemm_usm_mklcpu_cublas.cpp)
+  # Create a CMake target with one source file
+  add_executable(${EXAMPLE_TARGET} gemm_usm_generic.cpp)
 
-# Linking against onemath_blas_mklcpu and onemath_blas_cublas in CMake will add the required include directories and dependencies.
-# One can also link against `onemath_blas` to link against all the blas backends built.
-# These targets should only be used for compile-time dispatching.
-target_link_libraries(${EXAMPLE_TARGET} PUBLIC
-  onemath_blas_mklcpu
-  onemath_blas_cublas
-)
+  # Linking against onemath_blas_generic in CMake will add the required include directories and dependencies.
+  # This target should only be used for compile-time dispatching.
+  target_link_libraries(${EXAMPLE_TARGET} PUBLIC
+    onemath_blas_generic
+  )
 
-# Include directories specific to the examples
-target_include_directories(${EXAMPLE_TARGET} PUBLIC
-  ${PROJECT_SOURCE_DIR}/examples/include
-)
+  # Include directories specific to the examples
+  target_include_directories(${EXAMPLE_TARGET} PUBLIC
+    ${PROJECT_SOURCE_DIR}/examples/include
+  )
 
-# Register example as ctest
-add_test(NAME blas/EXAMPLE/CT/gemm_usm_mklcpu_cublas COMMAND ${EXAMPLE_TARGET})
+  # Register example as ctest
+  add_test(NAME blas/EXAMPLE/CT/gemm_usm_generic COMMAND ${EXAMPLE_TARGET})
+endif()