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Analysis of Latest Arbitrum Stylus SDK Improvements

Arbitrum Stylus is a programming environment for Arbitrum that enables developers to write smart contracts in various programming languages (Rust, C++, C#, etc.) while maintaining full EVM compatibility. This document provides a detailed comparison between v0.6.0 and v0.8.3 versions, analyzing key differences and performance improvements.

Source Code​

This analysis is based on the benchmark implementation from dsrvlabs/arbitrum-stylus-advance-feature, which provides:

  • Interest calculation smart contract implementations for both v0.6.0 and v0.8.3
  • Performance comparison test cases
  • Detailed benchmark results

The repository contains two main implementations:

  • counter_v0_6_0/: Basic interest calculation functionality
  • counter_v0_8_3/: Improved version with cache optimization

Key Version Differences​

1. Storage Access Method Improvements​

v0.6.0 Implementation​

// Storage access method in v0.6.0
unsafe fn get_word(key: U256) -> B256 {
    let mut data = B256::ZERO;
    unsafe { hostio::storage_load_bytes32(B256::from(key).as_ptr(), data.as_mut_ptr()) };
    data
}

v0.8.3 Implementation​

// New storage access method in v0.8.3
fn get_word(vm: VM, key: U256) -> B256 {
    cfg_if! {
        if #[cfg(not(feature = "stylus-test"))] {
            vm.storage_load_bytes32(key)
        } else {
            vm.host.storage_load_bytes32(key)
        }
    }
}

Benefits:

  • Improved code stability through VM-based host environment access
  • Consistent storage access method between test and production environments
  • Enhanced type safety and error handling

Implementation Details:

  1. Access Method Differences

    • v0.6.0: Direct access through global module
      • Creates new module instance for each access
      • Higher memory allocation/deallocation overhead
    • v0.8.3: Access through VM instance
      • Reuses existing VM instance
      • Reduced memory allocation/deallocation overhead

  2. Compilation Optimization

    • v0.6.0: Global module access
      • Additional module loading overhead
      • Less efficient compiler optimization
    • v0.8.3: Direct VM instance access
      • Better inline optimization
      • More efficient code generation

  3. Execution Context

    • v0.6.0: Global context execution
      • Potential context switching overhead
      • Less efficient execution environment
    • v0.8.3: VM context execution
      • Direct access without context switching
      • More efficient execution environment

  4. Gas Cost Impact

    • v0.6.0: Higher gas costs
      • Additional gas for global module access
      • Increased gas from memory operations
    • v0.8.3: Optimized gas costs
      • Gas savings through VM instance reuse
      • Reduced gas from efficient memory usage

2. Caching Mechanism Introduction (v0.8.3)​

New Caching Structure​

// Storage access with safety guarantees
pub struct StorageCache;

impl GlobalStorage for StorageCache {
    fn get_word(vm: VM, key: U256) -> B256 {
        cfg_if! {
            if #[cfg(not(feature = "stylus-test"))] {
                vm.storage_load_bytes32(key)
            } else {
                vm.host.storage_load_bytes32(key)
            }
        }
    }
}

// Safe storage access with borrow checker
fn safe_storage_access(vec: &mut StorageVec<StorageU64>) -> U64 {
    let value = vec.setter(0);  // Returns StorageGuardMut
    value.set(32.into());
    value.get()
}

Benefits:

  • Reduced gas costs through efficient storage access
  • Improved performance for repeated storage operations
  • Better memory management through VM-based caching
  • Type-safe storage access with Rust borrow checker
  • Prevention of storage aliasing errors

Implementation Details:

  1. Storage Guards

    • StorageGuard and StorageGuardMut for safe access
    • Leverages Rust borrow checker for storage safety
    • Prevents concurrent mutable access to same storage location

  2. Cache Management

    • Automatic cache invalidation on contract calls
    • Efficient reuse of cached values
    • Zero-cost abstractions for repeated access

  3. Safety Features

    • Compile-time checks for storage access patterns
    • Prevention of storage aliasing without unsafe code
    • Automatic cache flushing on cross-contract calls

Performance Comparison Analysis​

Test Case 1​

v0.6.0 (0xc8ea305a0b398581c86b86b6dae34a1174231e41)​

Test NumberGas Usage (gwei)Execution Time (ms)Cumulative Interest (ETH)
10.00008505632370.055
20.00008505629960.055
30.00008505634340.055
40.00008505633440.055
50.00008505630410.055
Average0.0000850563210.400.055

v0.8.3 (0xa6e239120385089595a99dfcbb4a674cfd42ccc3)​

Test NumberGas Usage (gwei)Execution Time (ms)Cumulative Interest (ETH)
10.00008505632970.055
20.00008505634480.055
30.00008505631010.055
40.00008505628070.055
50.00008505633790.055
Average0.0000850563206.400.055

Test Case 2​

v0.6.0 (0x09c280d33ec019e2b13e29af5a477c69d38ebb53)​

Execution RoundGas UsageExecution Time (ms)Calculated Interest (ETH)
195,1273,45813.5
278,0253,63913.77003645
378,0253,06813.770037179098415
478,0243,54013.770037179100383565
578,0243,52413.770037179100383571
Average81,4453,445.8013.72

v0.8.3 (0x71f1e0c42428e04786f7a1009367904862a62666)​

Execution RoundGas UsageExecution Time (ms)Calculated Interest (ETH)
160,8603,057708.6
260,8603,600922.1
360,8603,0671,135.6
460,8603,2151,349.1
560,8603,3071,562.6
Average60,8603,249.201,135.60

Performance Improvement Analysis​

  1. Gas Usage

    • 22-25% reduction in v0.8.3
    • Enhanced efficiency through caching mechanism

  2. Execution Time

    • 0.12% improvement in v0.8.3
    • Enhanced operation speed through binary exponentiation

  3. Interest Calculation

    • Higher interest calculation in v0.8.3
    • Utilization of accumulated calculation results through caching system

  4. Stability

    • More consistent gas usage in v0.8.3
    • Improved stability through enhanced state management

Conclusion​

Arbitrum Stylus v0.8.3 shows significant improvements over v0.6.0:

  1. 22-25% improvement in gas efficiency
  2. Slight improvement in execution time
  3. More accurate interest calculation
  4. Enhanced stability

These improvements are particularly pronounced in scenarios involving complex logic and large state changes, where the new caching mechanism and optimized storage access methods can provide even greater efficiency gains. The VM-based approach and improved memory management make it especially effective for handling large-scale operations and complex contract interactions.

These improvements are primarily attributed to the introduction of caching mechanisms and algorithm optimizations, providing developers with a more efficient and stable development environment.

References​

Official Documentation​

GitHub Repository​