CrossOver by CodeWeavers is a commercial compatibility layer that runs Windows applications on macOS without needing a Windows license or virtual machine.
Steps:
Pros: Native-like speed, low memory usage, no Windows license required. Cons: Some USB driver issues with older cutters (Graphtec, Roland, Mimaki).
For the breakout local search (BLS) heuristic—a state-of-the-art method for MaxCut—the application spawns multiple search threads using GCD’s concurrent queues. Each thread explores a different random perturbation of the current cut, and atomic operations update a global best solution. On a Mac Studio with 16 performance cores, BLS can process graphs with 10,000 nodes and 500,000 edges in under 30 seconds, yielding cuts within 1% of known optima. maxcut for mac
This is a full-featured sign-making suite for Mac. It includes design tools, nesting, and direct cutting.
I ran a quick test on a 500-node Erdős–Rényi graph:
| Method | Time (s) | Cut quality (% of optimum) | |----------------|----------|----------------------------| | Python brute | ∞ (crashed) | - | | GW (cvxpy) | 1.2 | 89% | | C++ GW | 0.08 | 90% | | C++ Burer–Monteiro | 0.25 | 94% | CrossOver by CodeWeavers is a commercial compatibility layer
Verdict: Use Python for prototyping, C++ for production.
MaxCut for Mac is built on a clear premise: high-performance optimization should not require command-line expertise. The application’s interface, written entirely in SwiftUI, offers:
Under the hood, however, lies sophisticated engineering. The SDP solver, typically a bottleneck, has been reimplemented using Apple’s Accelerate framework for BLAS/LAPACK operations and Metal Performance Shaders for eigenvalue decomposition. On an M2 Max MacBook Pro, graphs with up to 1,000 nodes can be approximated to within 95% of optimality in under two seconds—a task that would take tens of seconds on a comparable Windows laptop using generic Python libraries. Pros: Native-like speed, low memory usage, no Windows
Solution: On macOS, open System Settings > Privacy & Security > Full Disk Access, and allow Parallels or CrossOver. Then in Windows, install the cutter’s driver manually (often found on the manufacturer’s website for Windows 10).
Memory management is critical when dealing with dense graphs. MaxCut for Mac uses Swift’s value types and copy-on-write semantics to store adjacency matrices. For sparse graphs, it falls back to a compressed sparse row (CSR) format implemented in Swift with manual memory allocation via UnsafeMutableBufferPointer, ensuring no leaks while avoiding the overhead of ARC for bulk operations.