Fix three issues in the binary trie NodeIterator:
1. Empty nodes now properly backtrack to parent and continue iteration
instead of terminating the entire walk early.
2. `HashedNode` resolver handles `nil` data (all-zeros hash) gracefully
by treating it as Empty rather than panicking.
3. Parent update after node resolution guards against stack underflow
when resolving the root node itself.
---------
Co-authored-by: tellabg <249254436+tellabg@users.noreply.github.com>
## Summary
At tree depths below `log2(NumCPU)` (clamped to [2, 8]), hash the left
subtree in a goroutine while hashing the right subtree inline. This
exploits available CPU cores for the top levels of the tree where
subtree hashing is most expensive. On single-core machines, the parallel
path is disabled entirely.
Deeper nodes use sequential hashing with the existing `sync.Pool` hasher
where goroutine overhead would exceed the hash computation cost. The
parallel path uses `sha256.Sum256` with a stack-allocated buffer to
avoid pool contention across goroutines.
**Safety:**
- Left/right subtrees are disjoint — no shared mutable state
- `sync.WaitGroup` provides happens-before guarantee for the result
- `defer wg.Done()` + `recover()` prevents goroutine panics from
crashing the process
- `!bt.mustRecompute` early return means clean nodes never enter the
parallel path
- Hash results are deterministic regardless of computation order — no
consensus risk
## Benchmark (AMD EPYC 48-core, 500K entries, `--benchtime=10s
--count=3`, post-H01 baseline)
| Metric | Baseline | Parallel | Delta |
|--------|----------|----------|-------|
| Approve (Mgas/s) | 224.5 ± 7.1 | **259.6 ± 2.4** | **+15.6%** |
| BalanceOf (Mgas/s) | 982.9 ± 5.1 | 954.3 ± 10.8 | -2.9% (noise, clean
nodes skip parallel path) |
| Allocs/op (approve) | ~810K | ~700K | -13.6% |
Binary tree hashing is quite slow, owing to many factors. One of them is
the GC pressure that is the consequence of allocating many hashers, as a
binary tree has 4x the size of an MPT. This PR introduces an
optimization that already exists for the MPT: keep a pool of hashers, in
order to reduce the amount of allocations.
This is an optimization that existed for verkle and the MPT, but that
got dropped during the rebase.
Mark the nodes that were modified as needing recomputation, and skip the
hash computation if this is not needed. Otherwise, the whole tree is
hashed, which kills performance.
The computation of `MAIN_STORAGE_OFFSET` was incorrect, causing the last
byte of the stem to be dropped. This means that there would be a
collision in the hash computation (at the preimage level, not a hash
collision of course) if two keys were only differing at byte 31.
GetStorage and DeleteStorage used GetBinaryTreeKey to compute the tree
key, while UpdateStorage used GetBinaryTreeKeyStorageSlot. The latter
applies storage slot remapping (header offset for slots <64, main
storage prefix for the rest), so reads and deletes were targeting
different tree locations than writes.
Replace GetBinaryTreeKey with GetBinaryTreeKeyStorageSlot in both
GetStorage and DeleteStorage to match UpdateStorage. Add a regression
test that verifies the write→read→delete→read round-trip for main
storage slots.
The `Witness` method was not implemented for the binary tree, which
caused `debug_excutionWitness` to panic. This PR fixes that.
Note that the `TransitionTrie` version isn't implemented, and that's on
purpose: more thought must be given to what should go in the global
witness.
Based on [EIP-7864](https://eips.ethereum.org/EIPS/eip-7864), the tree
index should be 32 bytes instead of 31 bytes.
```
def get_tree_key(address: Address32, tree_index: int, sub_index: int):
# Assumes STEM_SUBTREE_WIDTH = 256
return tree_hash(address + tree_index.to_bytes(32, "little"))[:31] + bytes(
[sub_index]
)
```
In order to reduce the amount of code that is embedded into the keeper
binary, I am removing all the verkle code that uses go-verkle and
go-ipa. This will be followed by further PRs that are more like stubs to
replace code when the keeper build is detected.
I'm keeping the binary tree of course. This means that you will still
see `isVerkle` variables all over the codebase, but they will be renamed
when code is touched (i.e. this is not an invitation for 30+ AI slop
PRs).
---------
Co-authored-by: Gary Rong <garyrong0905@gmail.com>
This is broken off of #31730 to only focus on testing networks that
start with verkle at genesis.
The PR has seen a lot of work since its creation, and it now targets
creating and re-executing tests for a binary tree testnet without the
transition (so it starts at genesis). The transition tree has been moved
to its own package. It also replaces verkle with the binary tree for
this specific application.
---------
Co-authored-by: Gary Rong <garyrong0905@gmail.com>
Implement the binary tree as specified in [eip-7864](https://eips.ethereum.org/EIPS/eip-7864).
This will gradually replace verkle trees in the codebase. This is only
running the tests and will not be executed in production, but will help
me rebase some of my work, so that it doesn't bitrot as much.
---------
Signed-off-by: Guillaume Ballet
Co-authored-by: Parithosh Jayanthi <parithosh.jayanthi@ethereum.org>
Co-authored-by: rjl493456442 <garyrong0905@gmail.com>
