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[experimental] metal execution#6868

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a10y wants to merge 4 commits intodevelopfrom
metal
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[experimental] metal execution#6868
a10y wants to merge 4 commits intodevelopfrom
metal

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@a10y a10y commented Mar 10, 2026

just parking this here. performance is not that great, not coming anywhere close to saturating the memory bw on M4 Max

a10y added 4 commits March 4, 2026 11:17
Implements a new vortex-metal crate analogous to vortex-cuda that enables
GPU-accelerated array execution on Apple Silicon using the Metal framework.

Key components:
- MetalDeviceBuffer: DeviceBuffer implementation wrapping MTLBuffer
- MetalSession: Session managing Metal device, command queue, kernel registry
- MetalExecutionCtx: Execution context for kernel dispatch
- MetalLibraryLoader: Runtime shader compilation and caching
- FoRExecutor: Frame-of-Reference decoding kernel

Features:
- Runtime Metal shader compilation using objc2-metal
- Unified memory support for Apple Silicon (MTLStorageModeShared)
- Synchronous execution model (appropriate for unified memory)
- Full type support (u8-u64, i8-i64) for FoR decoding

Test Results:
- All 8 FoR decompression tests pass (signed and unsigned types)

Signed-off-by: Claude <claude@claude.ai>
Add FoR decompression benchmarks comparing Metal vs CPU performance.
Update plan.md with Phase 1 & 2 completion status and benchmark results.

Benchmark results show Metal and CPU achieving equivalent throughput
(~30-34 GiB/s) for FoR decoding, which is memory-bound. This validates
the Metal kernel launch overhead is minimal and unified memory works well.

Signed-off-by: Claude <claude@claude.ai>
Add a pure CPU benchmark for Frame-of-Reference (FoR) decompression
to enable comparison with GPU-accelerated implementations (vortex-metal,
vortex-cuda).

Benchmark results on M3 Max show ~33-38 GB/s throughput for all integer
types, which is near memory bandwidth limits - consistent with Metal
benchmark results showing CPU/GPU parity for this memory-bound operation.

Signed-off-by: Claude <claude@claude.ai>
Add benchmark variant that pre-loads data on GPU to isolate kernel
execution time from buffer allocation overhead.

Results show no difference between preloaded and with-copy variants
on Apple Silicon due to unified memory - buffer creation is the only
overhead, not actual data transfer.

Throughput remains ~34 GiB/s (vs ~400 GB/s theoretical), indicating
remaining overhead is in command buffer submission and kernel dispatch
latency, not memory bandwidth.

Signed-off-by: Claude <claude@claude.ai>
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