impalajit, hipsycl, tandem: various updates (#45013)

var/spack/repos/builtin/packages/hipsolver/package.py

@@ -139,6 +139,7 @@ def setup_build_environment(self, env):
     def cmake_args(self):
         args = [
             self.define("BUILD_CLIENTS_SAMPLES", "OFF"),
+            self.define("BUILD_FORTRAN_BINDINGS", "OFF"),
             self.define("BUILD_CLIENTS_TESTS", self.run_tests),
             self.define("SUITE_SPARSE_PATH", self.spec["suite-sparse"].prefix),
             self.define("ROCBLAS_PATH", self.spec["rocblas"].prefix),

var/spack/repos/builtin/packages/hipsycl/package.py

@@ -47,8 +47,10 @@ class Hipsycl(CMakePackage, ROCmPackage):
     # hipSYCL 0.8.0 supported only LLVM 8-10:
     # (https://github.com/AdaptiveCpp/AdaptiveCpp/blob/v0.8.0/CMakeLists.txt#L29-L37)
     depends_on("llvm@8:10", when="@0.8.0")
+    # https://github.com/spack/spack/issues/45029 and https://github.com/spack/spack/issues/43142
+    conflicts("^gcc@12", when="@23.10.0")
     # https://github.com/OpenSYCL/OpenSYCL/pull/918 was introduced after 0.9.4
-    conflicts("^llvm@16:", when="@:0.9.4")
+    conflicts("^gcc@12.2.0", when="@:0.9.4")
     # LLVM PTX backend requires cuda7:10.1 (https://tinyurl.com/v82k5qq)
     depends_on("cuda@9:10.1", when="@0.8.1: +cuda ^llvm@9")
     depends_on("cuda@9:", when="@0.8.1: +cuda ^llvm@10:")
@@ -161,7 +163,7 @@ def adjust_core_config(config):
             #    the libc++.so and libc++abi.so dyn linked to the sycl
             #    ptx backend
             rpaths = set()
-            if spec.satisfies("~rocm"):
+            if self.spec.satisfies("~rocm"):
                 so_paths = filesystem.find_libraries(
                     "libc++", self.spec["llvm"].prefix, shared=True, recursive=True
                 )

var/spack/repos/builtin/packages/impalajit/package.py

@@ -46,7 +46,6 @@ def cmake_args(self):
         args.append(self.define_from_variant("SHARED_LIB", "shared"))
         args.append(self.define("TESTS", self.run_tests))
 
-        if self.compiler != "intel":
+        if not self.spec.satisfies("%intel"):
             args.append("-DINTEL_COMPILER=OFF")
-
         return args

var/spack/repos/builtin/packages/tandem/package.py

@@ -45,6 +45,7 @@ class Tandem(CMakePackage, CudaPackage, ROCmPackage):
         description="Minimum order of quadrature rule, 0 = automatic",
     )
     variant("libxsmm", default=False, description="Install libxsmm-generator")
+    variant("python", default=False, description="installs python and numpy")
 
     depends_on("mpi")
 
@@ -61,14 +62,35 @@ class Tandem(CMakePackage, CudaPackage, ROCmPackage):
     depends_on("eigen@3.4.0")
 
     depends_on("zlib-api")
-    depends_on("petsc@3.14.6:3.18.5 +int64 +mumps +scalapack memalign=32")
+    depends_on("petsc@3.16: +int64 +mumps +scalapack memalign=32")
-    depends_on("petsc@3.14.6:3.18.5 +int64 +mumps +scalapack +knl", when="target=skylake:")
+    depends_on("petsc +knl", when="target=skylake:")
-    depends_on("petsc@3.14.6:3.18.5 +int64 +mumps +scalapack memalign=32 +cuda", when="+cuda")
+
-    depends_on("petsc@3.14.6:3.18.5 +int64 +mumps +scalapack memalign=32 +rocm", when="+rocm")
+    with when("+cuda"):
+        for tgt in CudaPackage.cuda_arch_values:
+            depends_on(f"petsc +cuda cuda_arch={tgt}", when=f"+cuda cuda_arch={tgt}")
+    with when("+rocm"):
+        for tgt in ROCmPackage.amdgpu_targets:
+            depends_on(f"petsc +rocm amdgpu_target={tgt}", when=f"+rocm amdgpu_target={tgt}")
+
+    depends_on("python@3", type="build", when="+python")
+    depends_on("py-numpy", type="build", when="+python")
 
     # see https://github.com/TEAR-ERC/tandem/issues/45
     conflicts("%intel")
 
+    # GPU architecture requirements
+    conflicts(
+        "cuda_arch=none",
+        when="+cuda",
+        msg="A value for cuda_arch must be specified. Add cuda_arch=XX",
+    )
+
+    conflicts(
+        "amdgpu_target=none",
+        when="+rocm",
+        msg="A value for amdgpu_arch must be specified. Add amdgpu_arch=XX",
+    )
+
     def cmake_args(self):
         args = [
             self.define_from_variant("DOMAIN_DIMENSION", "domain_dimension"),