core: add linalg methods

nac3core/src/codegen/builtin_fns.rs

@@ -1,5 +1,5 @@
 use inkwell::types::BasicTypeEnum;
-use inkwell::values::BasicValueEnum;
+use inkwell::values::{BasicValue, BasicValueEnum, PointerValue};
 use inkwell::{FloatPredicate, IntPredicate, OptimizationLevel};
 use itertools::Itertools;
 
@@ -31,7 +31,6 @@ pub fn call_int32<'ctx, G: CodeGenerator + ?Sized>(
     let llvm_usize = generator.get_size_type(ctx.ctx);
 
     let (n_ty, n) = n;
-
     Ok(match n {
         BasicValueEnum::IntValue(n) if matches!(n.get_type().get_bit_width(), 1 | 8) => {
             debug_assert!(ctx.unifier.unioned(n_ty, ctx.primitives.bool));
@@ -1836,3 +1835,480 @@ pub fn call_numpy_nextafter<'ctx, G: CodeGenerator + ?Sized>(
         _ => unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty]),
     })
 }
+
+/// Allocates a struct with the fields specified by `out_matrices` and returns a pointer to it
+fn build_output_struct<'ctx>(
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    out_matrices: Vec<BasicValueEnum<'ctx>>,
+) -> PointerValue<'ctx> {
+    let field_ty =
+        out_matrices.iter().map(BasicValueEnum::get_type).collect::<Vec<BasicTypeEnum>>();
+    let out_ty = ctx.ctx.struct_type(&field_ty, false);
+    let out_ptr = ctx.builder.build_alloca(out_ty, "").unwrap();
+
+    for (i, v) in out_matrices.into_iter().enumerate() {
+        unsafe {
+            let ptr = ctx
+                .builder
+                .build_in_bounds_gep(
+                    out_ptr,
+                    &[
+                        ctx.ctx.i32_type().const_zero(),
+                        ctx.ctx.i32_type().const_int(i as u64, false),
+                    ],
+                    "",
+                )
+                .unwrap();
+            ctx.builder.build_store(ptr, v).unwrap();
+        }
+    }
+    out_ptr
+}
+
+/// Invokes the `np_dot` using `nalgebra` crate
+pub fn call_np_dot<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+    x2: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "np_dot";
+    let (x1_ty, x1) = x1;
+    let (x2_ty, x2) = x2;
+
+    if let (BasicValueEnum::PointerValue(_), BasicValueEnum::PointerValue(_)) = (x1, x2) {
+        let (n1_elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, n1_elem_ty);
+        let (n2_elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty);
+        let n2_elem_ty = ctx.get_llvm_type(generator, n2_elem_ty);
+
+        let (BasicTypeEnum::FloatType(_), BasicTypeEnum::FloatType(_)) = (n1_elem_ty, n2_elem_ty)
+        else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        Ok(extern_fns::call_np_dot(ctx, x1, x2, None).into())
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty])
+    }
+}
+
+/// Invokes the `np_linalg_matmul` using `nalgebra` crate
+pub fn call_np_linalg_matmul<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+    x2: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "np_linalg_matmul";
+    let (x1_ty, x1) = x1;
+    let (x2_ty, x2) = x2;
+
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    if let (BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) = (x1, x2) {
+        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
+        let (n2_elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty);
+        let n2_elem_ty = ctx.get_llvm_type(generator, n2_elem_ty);
+
+        let (BasicTypeEnum::FloatType(_), BasicTypeEnum::FloatType(_)) = (n1_elem_ty, n2_elem_ty)
+        else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n2 = NDArrayValue::from_ptr_val(n2, llvm_usize, None);
+
+        let outdim0 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
+                .into_int_value()
+        };
+        let outdim1 = unsafe {
+            n2.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
+                .into_int_value()
+        };
+
+        let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[outdim0, outdim1])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+
+        extern_fns::call_np_linalg_matmul(ctx, x1, x2, out, None);
+        Ok(out)
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty])
+    }
+}
+
+/// Invokes the `np_linalg_cholesky` using `nalgebra` crate
+pub fn call_np_linalg_cholesky<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "np_linalg_cholesky";
+    let (x1_ty, x1) = x1;
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    if let BasicValueEnum::PointerValue(n1) = x1 {
+        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
+
+        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let dim0 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
+                .into_int_value()
+        };
+        let dim1 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
+                .into_int_value()
+        };
+
+        let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim1])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+
+        extern_fns::call_np_linalg_cholesky(ctx, x1, out, None);
+        Ok(out)
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty])
+    }
+}
+
+/// Invokes the `np_linalg_qr` using `nalgebra` crate
+pub fn call_np_linalg_qr<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "np_linalg_qr";
+    let (x1_ty, x1) = x1;
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    if let BasicValueEnum::PointerValue(n1) = x1 {
+        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
+
+        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let dim0 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
+                .into_int_value()
+        };
+        let dim1 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
+                .into_int_value()
+        };
+        let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
+
+        let out_q = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, k])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+        let out_r = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k, dim1])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+
+        extern_fns::call_np_linalg_qr(ctx, x1, out_q, out_r, None);
+
+        let out_ptr = build_output_struct(ctx, vec![out_q, out_r]);
+
+        Ok(ctx.builder.build_load(out_ptr, "QR_Factorization_result").map(Into::into).unwrap())
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty])
+    }
+}
+
+/// Invokes the `np_linalg_svd` using `nalgebra` crate
+pub fn call_np_linalg_svd<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "np_linalg_svd";
+    let (x1_ty, x1) = x1;
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    if let BasicValueEnum::PointerValue(n1) = x1 {
+        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
+
+        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+
+        let dim0 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
+                .into_int_value()
+        };
+        let dim1 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
+                .into_int_value()
+        };
+        let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
+
+        let out_u = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+        let out_s = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+        let out_vh = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim1, dim1])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+
+        extern_fns::call_np_linalg_svd(ctx, x1, out_u, out_s, out_vh, None);
+
+        let out_ptr = build_output_struct(ctx, vec![out_u, out_s, out_vh]);
+
+        Ok(ctx.builder.build_load(out_ptr, "SVD_Factorization_result").map(Into::into).unwrap())
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty])
+    }
+}
+
+/// Invokes the `np_linalg_inv` using `nalgebra` crate
+pub fn call_np_linalg_inv<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "np_linalg_inv";
+    let (x1_ty, x1) = x1;
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    if let BasicValueEnum::PointerValue(n1) = x1 {
+        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
+
+        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let dim0 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
+                .into_int_value()
+        };
+        let dim1 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
+                .into_int_value()
+        };
+
+        let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim1])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+
+        extern_fns::call_np_linalg_inv(ctx, x1, out, None);
+        Ok(out)
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty])
+    }
+}
+
+/// Invokes the `np_linalg_pinv` using `nalgebra` crate
+pub fn call_np_linalg_pinv<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "np_linalg_pinv";
+    let (x1_ty, x1) = x1;
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    if let BasicValueEnum::PointerValue(n1) = x1 {
+        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
+
+        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+
+        let dim0 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
+                .into_int_value()
+        };
+        let dim1 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
+                .into_int_value()
+        };
+
+        let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim1, dim0])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+
+        extern_fns::call_np_linalg_pinv(ctx, x1, out, None);
+        Ok(out)
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty])
+    }
+}
+
+/// Invokes the `sp_linalg_lu` using `nalgebra` crate
+pub fn call_sp_linalg_lu<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "sp_linalg_lu";
+    let (x1_ty, x1) = x1;
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    if let BasicValueEnum::PointerValue(n1) = x1 {
+        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
+
+        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+
+        let dim0 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
+                .into_int_value()
+        };
+        let dim1 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
+                .into_int_value()
+        };
+        let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
+
+        let out_l = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, k])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+        let out_u = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k, dim1])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+
+        extern_fns::call_sp_linalg_lu(ctx, x1, out_l, out_u, None);
+
+        let out_ptr = build_output_struct(ctx, vec![out_l, out_u]);
+        Ok(ctx.builder.build_load(out_ptr, "LU_Factorization_result").map(Into::into).unwrap())
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty])
+    }
+}
+
+/// Invokes the `sp_linalg_schur` using `nalgebra` crate
+pub fn call_sp_linalg_schur<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "sp_linalg_schur";
+    let (x1_ty, x1) = x1;
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    if let BasicValueEnum::PointerValue(n1) = x1 {
+        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
+
+        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+
+        let dim0 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
+                .into_int_value()
+        };
+        let out_t = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+        let out_z = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+
+        extern_fns::call_sp_linalg_schur(ctx, x1, out_t, out_z, None);
+
+        let out_ptr = build_output_struct(ctx, vec![out_t, out_z]);
+        Ok(ctx.builder.build_load(out_ptr, "Schur_Factorization_result").map(Into::into).unwrap())
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty])
+    }
+}
+
+/// Invokes the `sp_linalg_hessenberg` using `nalgebra` crate
+pub fn call_sp_linalg_hessenberg<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    x1: (Type, BasicValueEnum<'ctx>),
+) -> Result<BasicValueEnum<'ctx>, String> {
+    const FN_NAME: &str = "sp_linalg_hessenberg";
+    let (x1_ty, x1) = x1;
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    if let BasicValueEnum::PointerValue(n1) = x1 {
+        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
+        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
+
+        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
+            unimplemented!("{FN_NAME} operates on float type NdArrays only");
+        };
+
+        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+
+        let dim0 = unsafe {
+            n1.dim_sizes()
+                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
+                .into_int_value()
+        };
+        let out_h = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+        let out_q = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
+            .unwrap()
+            .as_base_value()
+            .as_basic_value_enum();
+        extern_fns::call_sp_linalg_hessenberg(ctx, x1, out_h, out_q, None);
+
+        let out_ptr = build_output_struct(ctx, vec![out_h, out_q]);
+        Ok(ctx
+            .builder
+            .build_load(out_ptr, "Hessenberg_decomposition_result")
+            .map(Into::into)
+            .unwrap())
+    } else {
+        unsupported_type(ctx, FN_NAME, &[x1_ty])
+    }
+}

nac3core/src/codegen/extern_fns.rs

@@ -130,3 +130,91 @@ pub fn call_ldexp<'ctx>(
         .map(Either::unwrap_left)
         .unwrap()
 }
+
+/// Macro to generate `np_linalg` and `sp_linalg` functions
+/// The function takes as input `NDArray` and returns ()
+///
+/// Arguments:
+/// * `$fn_name:ident`: The identifier of the rust function to be generated
+/// * `$extern_fn:literal`: Name of underlying extern function
+/// * (2/3/4): Number of `NDArray` that function takes as input
+///
+/// Note:
+/// The operands and resulting `NDArray` are both passed as input to the funcion
+/// It is the responsibility of caller to ensure that output `NDArray` is properly allocated on stack
+/// The function changes the content of the output `NDArray` in-place
+macro_rules! generate_linalg_extern_fn {
+    ($fn_name:ident, $extern_fn:literal, 2) => {
+        generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2);
+    };
+    ($fn_name:ident, $extern_fn:literal, 3) => {
+        generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2, mat3);
+    };
+    ($fn_name:ident, $extern_fn:literal, 4) => {
+        generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2, mat3, mat4);
+    };
+    ($fn_name:ident, $extern_fn:literal $(,$input_matrix:ident)*) => {
+        #[doc = concat!("Invokes the linalg `", stringify!($extern_fn), " function." )]
+        pub fn $fn_name<'ctx>(
+            ctx: &mut CodeGenContext<'ctx, '_>
+            $(,$input_matrix: BasicValueEnum<'ctx>)*,
+            name: Option<&str>,
+        ){
+            const FN_NAME: &str = $extern_fn;
+            let extern_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
+                let fn_type = ctx.ctx.void_type().fn_type(&[$($input_matrix.get_type().into()),*], false);
+
+                let func = ctx.module.add_function(FN_NAME, fn_type, None);
+                for attr in ["mustprogress", "nofree", "nounwind", "willreturn", "writeonly"] {
+                    func.add_attribute(
+                        AttributeLoc::Function,
+                        ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
+                    );
+                }
+                func
+            });
+
+            ctx.builder.build_call(extern_fn, &[$($input_matrix.into(),)*], name.unwrap_or_default()).unwrap();
+        }
+    };
+}
+
+generate_linalg_extern_fn!(call_np_linalg_matmul, "np_linalg_matmul", 3);
+generate_linalg_extern_fn!(call_np_linalg_cholesky, "np_linalg_cholesky", 2);
+generate_linalg_extern_fn!(call_np_linalg_qr, "np_linalg_qr", 3);
+generate_linalg_extern_fn!(call_np_linalg_svd, "np_linalg_svd", 4);
+generate_linalg_extern_fn!(call_np_linalg_inv, "np_linalg_inv", 2);
+generate_linalg_extern_fn!(call_np_linalg_pinv, "np_linalg_pinv", 2);
+generate_linalg_extern_fn!(call_sp_linalg_lu, "sp_linalg_lu", 3);
+generate_linalg_extern_fn!(call_sp_linalg_schur, "sp_linalg_schur", 3);
+generate_linalg_extern_fn!(call_sp_linalg_hessenberg, "sp_linalg_hessenberg", 3);
+
+/// Invokes the linalg `np_dot` function.
+pub fn call_np_dot<'ctx>(
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    mat1: BasicValueEnum<'ctx>,
+    mat2: BasicValueEnum<'ctx>,
+    name: Option<&str>,
+) -> FloatValue<'ctx> {
+    const FN_NAME: &str = "np_dot";
+
+    let extern_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
+        let fn_type =
+            ctx.ctx.f64_type().fn_type(&[mat1.get_type().into(), mat2.get_type().into()], false);
+        let func = ctx.module.add_function(FN_NAME, fn_type, None);
+        for attr in ["mustprogress", "nofree", "nounwind", "willreturn", "writeonly"] {
+            func.add_attribute(
+                AttributeLoc::Function,
+                ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
+            );
+        }
+        func
+    });
+
+    ctx.builder
+        .build_call(extern_fn, &[mat1.into(), mat2.into()], name.unwrap_or_default())
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_float_value))
+        .map(Either::unwrap_left)
+        .unwrap()
+}

nac3core/src/codegen/numpy.rs

@@ -159,7 +159,7 @@ where
 ///
 /// * `elem_ty` - The element type of the `NDArray`.
 /// * `shape` - The shape of the `NDArray`, represented am array of [`IntValue`]s.
-fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
+pub fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
     elem_ty: Type,

nac3core/src/toplevel/builtins.rs

@@ -556,6 +556,17 @@ impl<'a> BuiltinBuilder<'a> {
             | PrimDef::FunNpLdExp
             | PrimDef::FunNpHypot
             | PrimDef::FunNpNextAfter => self.build_np_2ary_function(prim),
+
+            PrimDef::FunNpDot
+            | PrimDef::FunNpLinalgMatmul
+            | PrimDef::FunNpLinalgCholesky
+            | PrimDef::FunNpLinalgQr
+            | PrimDef::FunNpLinalgSvd
+            | PrimDef::FunNpLinalgInv
+            | PrimDef::FunNpLinalgPinv
+            | PrimDef::FunSpLinalgLu
+            | PrimDef::FunSpLinalgSchur
+            | PrimDef::FunSpLinalgHessenberg => self.build_linalg_methods(prim),
         };
 
         if cfg!(debug_assertions) {
@@ -1874,6 +1885,150 @@ impl<'a> BuiltinBuilder<'a> {
         }
     }
 
+    /// Build `np_linalg` and `sp_linalg` functions
+    ///
+    /// The input to these functions must be floating point `NDArray`
+    fn build_linalg_methods(&mut self, prim: PrimDef) -> TopLevelDef {
+        debug_assert_prim_is_allowed(
+            prim,
+            &[
+                PrimDef::FunNpDot,
+                PrimDef::FunNpLinalgMatmul,
+                PrimDef::FunNpLinalgCholesky,
+                PrimDef::FunNpLinalgQr,
+                PrimDef::FunNpLinalgSvd,
+                PrimDef::FunNpLinalgInv,
+                PrimDef::FunNpLinalgPinv,
+                PrimDef::FunSpLinalgLu,
+                PrimDef::FunSpLinalgSchur,
+                PrimDef::FunSpLinalgHessenberg,
+            ],
+        );
+
+        match prim {
+            PrimDef::FunNpDot => create_fn_by_codegen(
+                self.unifier,
+                &self.num_or_ndarray_var_map,
+                prim.name(),
+                self.primitives.float,
+                &[(self.num_or_ndarray_ty.ty, "x1"), (self.num_or_ndarray_ty.ty, "x2")],
+                Box::new(move |ctx, _, fun, args, generator| {
+                    let x1_ty = fun.0.args[0].ty;
+                    let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
+                    let x2_ty = fun.0.args[1].ty;
+                    let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
+
+                    Ok(Some(builtin_fns::call_np_dot(
+                        generator,
+                        ctx,
+                        (x1_ty, x1_val),
+                        (x2_ty, x2_val),
+                    )?))
+                }),
+            ),
+
+            PrimDef::FunNpLinalgMatmul => create_fn_by_codegen(
+                self.unifier,
+                &VarMap::new(),
+                prim.name(),
+                self.ndarray_float_2d,
+                &[(self.ndarray_float_2d, "x1"), (self.ndarray_float_2d, "x2")],
+                Box::new(move |ctx, _, fun, args, generator| {
+                    let x1_ty = fun.0.args[0].ty;
+                    let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
+                    let x2_ty = fun.0.args[1].ty;
+                    let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
+
+                    Ok(Some(builtin_fns::call_np_linalg_matmul(
+                        generator,
+                        ctx,
+                        (x1_ty, x1_val),
+                        (x2_ty, x2_val),
+                    )?))
+                }),
+            ),
+
+            PrimDef::FunNpLinalgCholesky | PrimDef::FunNpLinalgInv | PrimDef::FunNpLinalgPinv => {
+                create_fn_by_codegen(
+                    self.unifier,
+                    &VarMap::new(),
+                    prim.name(),
+                    self.ndarray_float_2d,
+                    &[(self.ndarray_float_2d, "x1")],
+                    Box::new(move |ctx, _, fun, args, generator| {
+                        let x1_ty = fun.0.args[0].ty;
+                        let x1_val =
+                            args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
+
+                        let func = match prim {
+                            PrimDef::FunNpLinalgCholesky => builtin_fns::call_np_linalg_cholesky,
+                            PrimDef::FunNpLinalgInv => builtin_fns::call_np_linalg_inv,
+                            PrimDef::FunNpLinalgPinv => builtin_fns::call_np_linalg_pinv,
+                            _ => unreachable!(),
+                        };
+                        Ok(Some(func(generator, ctx, (x1_ty, x1_val))?))
+                    }),
+                )
+            }
+
+            PrimDef::FunNpLinalgQr
+            | PrimDef::FunSpLinalgLu
+            | PrimDef::FunSpLinalgSchur
+            | PrimDef::FunSpLinalgHessenberg => {
+                let ret_ty = self.unifier.add_ty(TypeEnum::TTuple {
+                    ty: vec![self.ndarray_float_2d, self.ndarray_float_2d],
+                });
+                create_fn_by_codegen(
+                    self.unifier,
+                    &VarMap::new(),
+                    prim.name(),
+                    ret_ty,
+                    &[(self.ndarray_float_2d, "x1")],
+                    Box::new(move |ctx, _, fun, args, generator| {
+                        let x1_ty = fun.0.args[0].ty;
+                        let x1_val =
+                            args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
+
+                        let func = match prim {
+                            PrimDef::FunNpLinalgQr => builtin_fns::call_np_linalg_qr,
+                            PrimDef::FunSpLinalgLu => builtin_fns::call_sp_linalg_lu,
+                            PrimDef::FunSpLinalgSchur => builtin_fns::call_sp_linalg_schur,
+                            PrimDef::FunSpLinalgHessenberg => {
+                                builtin_fns::call_sp_linalg_hessenberg
+                            }
+                            _ => unreachable!(),
+                        };
+                        Ok(Some(func(generator, ctx, (x1_ty, x1_val))?))
+                    }),
+                )
+            }
+
+            PrimDef::FunNpLinalgSvd => {
+                let ret_ty = self.unifier.add_ty(TypeEnum::TTuple {
+                    ty: vec![self.ndarray_float_2d, self.ndarray_float, self.ndarray_float_2d],
+                });
+                create_fn_by_codegen(
+                    self.unifier,
+                    &VarMap::new(),
+                    prim.name(),
+                    ret_ty,
+                    &[(self.ndarray_float_2d, "x1")],
+                    Box::new(move |ctx, _, fun, args, generator| {
+                        let x1_ty = fun.0.args[0].ty;
+                        let x1_val =
+                            args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
+
+                        Ok(Some(builtin_fns::call_np_linalg_svd(generator, ctx, (x1_ty, x1_val))?))
+                    }),
+                )
+            }
+            _ => {
+                println!("{:?}", prim.name());
+                unreachable!()
+            }
+        }
+    }
+
     fn create_method(prim: PrimDef, method_ty: Type) -> (StrRef, Type, DefinitionId) {
         (prim.simple_name().into(), method_ty, prim.id())
     }

nac3core/src/toplevel/helper.rs

@@ -100,6 +100,17 @@ pub enum PrimDef {
     FunNpHypot,
     FunNpNextAfter,
 
+    FunNpDot,
+    FunNpLinalgMatmul,
+    FunNpLinalgCholesky,
+    FunNpLinalgQr,
+    FunNpLinalgSvd,
+    FunNpLinalgInv,
+    FunNpLinalgPinv,
+    FunSpLinalgLu,
+    FunSpLinalgSchur,
+    FunSpLinalgHessenberg,
+
     // Miscellaneous Python & NAC3 functions
     FunInt32,
     FunInt64,
@@ -270,6 +281,16 @@ impl PrimDef {
             PrimDef::FunNpLdExp => fun("np_ldexp", None),
             PrimDef::FunNpHypot => fun("np_hypot", None),
             PrimDef::FunNpNextAfter => fun("np_nextafter", None),
+            PrimDef::FunNpDot => fun("np_dot", None),
+            PrimDef::FunNpLinalgMatmul => fun("np_linalg_matmul", None),
+            PrimDef::FunNpLinalgCholesky => fun("np_linalg_cholesky", None),
+            PrimDef::FunNpLinalgQr => fun("np_linalg_qr", None),
+            PrimDef::FunNpLinalgSvd => fun("np_linalg_svd", None),
+            PrimDef::FunNpLinalgInv => fun("np_linalg_inv", None),
+            PrimDef::FunNpLinalgPinv => fun("np_linalg_pinv", None),
+            PrimDef::FunSpLinalgLu => fun("sp_linalg_lu", None),
+            PrimDef::FunSpLinalgSchur => fun("sp_linalg_schur", None),
+            PrimDef::FunSpLinalgHessenberg => fun("sp_linalg_hessenberg", None),
 
             // Miscellaneous Python & NAC3 functions
             PrimDef::FunInt32 => fun("int32", None),