Failure to accelerate computing with a quadtree

Reproducing the behavior

Thank you very much for inventing such an amazing programming language. However, when I programmed a quadtree using Bend, I found that this code did not work properly.

Running command:

bend run-cu quadtree.bend -s

With code:

type Quadtree(T):
  TreeNode { ~nw: Quadtree(T), ~ne: Quadtree(T), ~sw: Quadtree(T), ~se: Quadtree(T) }
  TreeLeaf { value: T }

def sum(tree):
match tree:
  case Quadtree/TreeLeaf:
    return tree.value
  case Quadtree/TreeNode:
    return sum(tree.nw) + sum(tree.ne) + sum(tree.sw) + sum(tree.se)

def gen(n):
  if n == 0:
    return Quadtree/TreeLeaf{value: 1}
  else:
    return Quadtree/TreeNode{nw: gen(n - 1), ne: gen(n - 1), sw: gen(n - 1), se: gen(n - 1)}

def main():
  quadtree = gen(3)
  #  return quadtree
  return sum(quadtree)

Error:

The program fails to stop and no results are output.

Expected behavior:

Like:

Result: 64
- ITRS: 2819
- TIME: 0.00s
- MIPS: 1.04

System Settings

HVM: [HVM 2.0.22]
Bend: [Bend 0.2.37]
OS: [Linux (Ubuntu 24.04.1 LTS)]
CPU: [Intel(R) Xeon(R) Platinum 8352V CPU @ 2.10GHz]
GPU: [RTX 4090]
Cuda Version [release 12.1, V12.1.105]
GCC: [11.4.0]

Additional context

I have tried:

Reading the project documentation, I did not find detailed instructions on this problem.
Searching Issues, but did not find anything similar.

I found the program runs correctly with “bend run quadtree.bend -s”:

Result: 64
- ITRS: 2819
- TIME: 0.00s
- MIPS: 1.05

And for another program, using a binary tree to accelerate computing, runs correctly with “bend run-cu binaryree.bend -s":

type MyTree(T):
  Node { ~left: MyTree(T), ~right: MyTree(T) }
  Leaf { value: T }

def gen(n):
  if n == 0:
    return MyTree/Leaf{value : 1}
  else:
    return MyTree/Node{left: gen(n - 1), right: gen(n - 1) }

def sum(tree):
  match tree:
    case MyTree/Leaf:
      return tree.value
    case MyTree/Node:
      return sum(tree.left) + sum(tree.right)

def main():
  binarytree = gen(20)
  return sum(binarytree)

Bend is incredibly powerful, and I’m impressed by its remarkable speed:

Result: 1048576
- ITRS: 71335893
- LEAK: 12550783
- TIME: 0.03s
- MIPS: 2526.24

I really enjoy using this language and can’t wait to improve my algorithms, such as matrix multiplication. However, the implementation of quadtrees has been a persistent challenge for me.

My questions:

I don't know why this code fails to output results, even when the data size is small (n = 3). Is this because Quadtree has four member variables while MyTree has only two? These two pieces of code are really similar.
Does Bend support multi-parallelism? Like computing "return Quadtree/TreeNode{nw: gen(n - 1), ne: gen(n - 1), sw: gen(n - 1), se: gen(n - 1)}"?
If so, how should it be implemented?

Thank you very much for your time and help! I would greatly appreciate any help or guidance. Looking forward to hearing from you.

Best regards, Siyu Wang

HigherOrderCO / Bend