diff --git a/flang/lib/Optimizer/Transforms/CUFComputeSharedMemoryOffsetsAndSize.cpp b/flang/lib/Optimizer/Transforms/CUFComputeSharedMemoryOffsetsAndSize.cpp
index aec3ea294ac6c..dcb5f42902ee6 100644
--- a/flang/lib/Optimizer/Transforms/CUFComputeSharedMemoryOffsetsAndSize.cpp
+++ b/flang/lib/Optimizer/Transforms/CUFComputeSharedMemoryOffsetsAndSize.cpp
@@ -58,11 +58,13 @@ struct CUFComputeSharedMemoryOffsetsAndSize
     auto gpuMod = cuf::getOrCreateGPUModule(mod, symTab);
     mlir::Type i8Ty = builder.getI8Type();
     mlir::Type i32Ty = builder.getI32Type();
+    mlir::Type idxTy = builder.getIndexType();
     for (auto funcOp : gpuMod.getOps<mlir::gpu::GPUFuncOp>()) {
       unsigned nbDynamicSharedVariables = 0;
       unsigned nbStaticSharedVariables = 0;
       uint64_t sharedMemSize = 0;
       unsigned short alignment = 0;
+      mlir::Value crtDynOffset;
 
       // Go over each shared memory operation and compute their start offset and
       // the size and alignment of the global to be generated if all variables
@@ -73,16 +75,30 @@ struct CUFComputeSharedMemoryOffsetsAndSize
         builder.setInsertionPoint(sharedOp);
         if (fir::hasDynamicSize(sharedOp.getInType())) {
           mlir::Type ty = sharedOp.getInType();
-          // getTypeSizeAndAlignmentOrCrash will crash trying to compute the
-          // size of an array with dynamic size. Just get the alignment to
-          // create the global.
           if (auto seqTy = mlir::dyn_cast<fir::SequenceType>(ty))
             ty = seqTy.getEleTy();
           unsigned short align = dl->getTypeABIAlignment(ty);
-          ++nbDynamicSharedVariables;
-          mlir::Value zero = builder.createIntegerConstant(loc, i32Ty, 0);
-          sharedOp.getOffsetMutable().assign(zero);
           alignment = std::max(alignment, align);
+          uint64_t tySize = dl->getTypeSize(ty);
+          ++nbDynamicSharedVariables;
+          if (crtDynOffset) {
+            sharedOp.getOffsetMutable().assign(
+                builder.createConvert(loc, i32Ty, crtDynOffset));
+          } else {
+            mlir::Value zero = builder.createIntegerConstant(loc, i32Ty, 0);
+            sharedOp.getOffsetMutable().assign(zero);
+          }
+
+          mlir::Value dynSize =
+              builder.createIntegerConstant(loc, idxTy, tySize);
+          for (auto extent : sharedOp.getShape())
+            dynSize = builder.create<mlir::arith::MulIOp>(loc, dynSize, extent);
+          if (crtDynOffset)
+            crtDynOffset =
+                builder.create<mlir::arith::AddIOp>(loc, crtDynOffset, dynSize);
+          else
+            crtDynOffset = dynSize;
+
           continue;
         }
         auto [size, align] = fir::getTypeSizeAndAlignmentOrCrash(
diff --git a/flang/test/Fir/CUDA/cuda-shared-offset.mlir b/flang/test/Fir/CUDA/cuda-shared-offset.mlir
index 1eea75c802204..5e9aac4e71438 100644
--- a/flang/test/Fir/CUDA/cuda-shared-offset.mlir
+++ b/flang/test/Fir/CUDA/cuda-shared-offset.mlir
@@ -54,3 +54,56 @@ module attributes {dlti.dl_spec = #dlti.dl_spec<#dlti.dl_entry<!llvm.ptr, dense<
 // CHECK: fir.global internal @_QPshared_static__shared_mem(dense<0> : vector<28xi8>) {alignment = 8 : i64, data_attr = #cuf.cuda<shared>} : !fir.array<28xi8>
 // CHECK: }
 // CHECK: }
+
+// -----
+
+module attributes {dlti.dl_spec = #dlti.dl_spec<#dlti.dl_entry<!llvm.ptr, dense<64> : vector<4xi64>>, #dlti.dl_entry<!llvm.ptr<271>, dense<32> : vector<4xi64>>, #dlti.dl_entry<!llvm.ptr<270>, dense<32> : vector<4xi64>>, #dlti.dl_entry<f128, dense<128> : vector<2xi64>>, #dlti.dl_entry<f64, dense<64> : vector<2xi64>>, #dlti.dl_entry<f80, dense<128> : vector<2xi64>>, #dlti.dl_entry<f16, dense<16> : vector<2xi64>>, #dlti.dl_entry<i32, dense<32> : vector<2xi64>>, #dlti.dl_entry<i16, dense<16> : vector<2xi64>>, #dlti.dl_entry<i128, dense<128> : vector<2xi64>>, #dlti.dl_entry<i8, dense<8> : vector<2xi64>>, #dlti.dl_entry<!llvm.ptr<272>, dense<64> : vector<4xi64>>, #dlti.dl_entry<i64, dense<64> : vector<2xi64>>, #dlti.dl_entry<i1, dense<8> : vector<2xi64>>, #dlti.dl_entry<"dlti.endianness", "little">, #dlti.dl_entry<"dlti.stack_alignment", 128 : i64>>, fir.defaultkind = "a1c4d8i4l4r4", fir.kindmap = "", gpu.container_module, llvm.data_layout = "e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-i128:128-f80:128-n8:16:32:64-S128", llvm.ident = "flang version 20.0.0 (https://github.com/llvm/llvm-project.git cae351f3453a0a26ec8eb2ddaf773c24a29d929e)", llvm.target_triple = "x86_64-unknown-linux-gnu"} {
+  gpu.module @cuda_device_mod {
+    gpu.func @_QMmPshareddyn(%arg0: !fir.box<!fir.array<?x?xi32>> {cuf.data_attr = #cuf.cuda<device>, fir.bindc_name = "a"}, %arg1: !fir.box<!fir.array<?x?xi32>> {cuf.data_attr = #cuf.cuda<device>, fir.bindc_name = "b"}, %arg2: i32 {fir.bindc_name = "k"}) attributes {cuf.proc_attr = #cuf.cuda_proc<global>} {
+      %c1_i32 = arith.constant 1 : i32
+      %c2_i32 = arith.constant 2 : i32
+      %c0 = arith.constant 0 : index
+      %5 = fir.address_of(@_QM__fortran_builtinsE__builtin_blockdim) : !fir.ref<!fir.type<_QM__fortran_builtinsT__builtin_dim3{x:i32,y:i32,z:i32}>>
+      %6 = fir.declare %5 {uniq_name = "_QM__fortran_builtinsE__builtin_blockdim"} : (!fir.ref<!fir.type<_QM__fortran_builtinsT__builtin_dim3{x:i32,y:i32,z:i32}>>) -> !fir.ref<!fir.type<_QM__fortran_builtinsT__builtin_dim3{x:i32,y:i32,z:i32}>>
+      %15 = fir.alloca i32
+      %16 = fir.declare %15 {fortran_attrs = #fir.var_attrs<value>, uniq_name = "_QMmFss1Ek"} : (!fir.ref<i32>) -> !fir.ref<i32>
+      %27 = fir.coordinate_of %6, x : (!fir.ref<!fir.type<_QM__fortran_builtinsT__builtin_dim3{x:i32,y:i32,z:i32}>>) -> !fir.ref<i32>
+      %28 = fir.load %27 : !fir.ref<i32>
+      %29 = fir.convert %28 : (i32) -> i64
+      %30 = fir.convert %29 : (i64) -> index
+      %31 = arith.cmpi sgt, %30, %c0 : index
+      %32 = arith.select %31, %30, %c0 : index
+      %33 = fir.coordinate_of %6, y : (!fir.ref<!fir.type<_QM__fortran_builtinsT__builtin_dim3{x:i32,y:i32,z:i32}>>) -> !fir.ref<i32>
+      %34 = fir.load %33 : !fir.ref<i32>
+      %35 = fir.convert %34 : (i32) -> i64
+      %36 = fir.convert %35 : (i64) -> index
+      %37 = arith.cmpi sgt, %36, %c0 : index
+      %38 = arith.select %37, %36, %c0 : index
+      %39 = cuf.shared_memory !fir.array<?x?xi32>, %32, %38 : index, index {bindc_name = "s1", uniq_name = "_QMmFss1Es1"} -> !fir.ref<!fir.array<?x?xi32>>
+      %40 = fir.shape %32, %38 : (index, index) -> !fir.shape<2>
+      %41 = fir.declare %39(%40) {data_attr = #cuf.cuda<shared>, uniq_name = "_QMmFss1Es1"} : (!fir.ref<!fir.array<?x?xi32>>, !fir.shape<2>) -> !fir.ref<!fir.array<?x?xi32>>
+      %42 = fir.load %16 : !fir.ref<i32>
+      %43 = arith.muli %42, %c2_i32 : i32
+      %44 = fir.convert %43 : (i32) -> i64
+      %45 = fir.convert %44 : (i64) -> index
+      %46 = arith.cmpi sgt, %45, %c0 : index
+      %47 = arith.select %46, %45, %c0 : index
+      %48 = fir.load %16 : !fir.ref<i32>
+      %49 = fir.convert %48 : (i32) -> i64
+      %50 = fir.convert %49 : (i64) -> index
+      %51 = arith.cmpi sgt, %50, %c0 : index
+      %52 = arith.select %51, %50, %c0 : index
+      %53 = cuf.shared_memory !fir.array<?x?xi32>, %47, %52 : index, index {bindc_name = "s2", uniq_name = "_QMmFss1Es2"} -> !fir.ref<!fir.array<?x?xi32>>
+      gpu.return
+    }
+  }
+}
+
+// CHECK: gpu.func @_QMmPshareddyn(%arg0: !fir.box<!fir.array<?x?xi32>> {cuf.data_attr = #cuf.cuda<device>, fir.bindc_name = "a"}, %arg1: !fir.box<!fir.array<?x?xi32>> {cuf.data_attr = #cuf.cuda<device>, fir.bindc_name = "b"}, %arg2: i32 {fir.bindc_name = "k"}) attributes {cuf.proc_attr = #cuf.cuda_proc<global>} {
+// CHECK: %[[EXTENT0:.*]] = arith.select 
+// CHECK: %[[EXTENT1:.*]] = arith.select 
+// CHECK: %[[SIZE_EXTENT:.*]] = arith.muli %c4{{.*}}, %[[EXTENT0]] : index
+// CHECK: %[[DYNSIZE:.*]] = arith.muli %[[SIZE_EXTENT]], %[[EXTENT1]] : index
+// CHECK: cuf.shared_memory[%c0{{.*}} : i32] !fir.array<?x?xi32>, %9, %15 : index, index {bindc_name = "s1", uniq_name = "_QMmFss1Es1"} -> !fir.ref<!fir.array<?x?xi32>>
+// CHECK: %[[CONV_DYNSIZE:.*]] = fir.convert %[[DYNSIZE]] : (index) -> i32
+// CHECK: cuf.shared_memory[%[[CONV_DYNSIZE]] : i32] !fir.array<?x?xi32>, %26, %31 : index, index {bindc_name = "s2", uniq_name = "_QMmFss1Es2"} -> !fir.ref<!fir.array<?x?xi32>>