A playground for experimenting with Apple silicon GPUs and metal-rs bindings
- dotprod (ushort Vs. half impls).
- matmul (naive Vs. tiled impls)
Launching a metal compute kernel is a 2 step process.
# every kernel is self contained i.e. is its own crate. Simply `cd` into a kernel's directory and run
# the following, which compiles our shader to an intermediate representation using the metal utility
xcrun -sdk macosx metal -c ./src/shaders/dotprod.metal -o ./src/shaders/dotprod.air
# next, compile the .air file to generate a .metallib file - which I believe is LLVM IR (need confirmation)
xcrun -sdk macosx metallib ./src/metal/matrixprod.air -o ./src/metal/matrixprod.metallib
# lastly, run the rust binary to launch the kernel and examine its output.
cargo runcargo run
Finished dev [unoptimized + debuginfo] target(s) in 0.01s
Running `target/debug/mtl`
____*** vector dotprod of 1,000,000 elements of type `ushort` ***___
Dotprod on CPU
Done in 15.48ms
Dotprod on CPU - parallel
Done in 3.38ms
Dotprod on GPU
Actual time spent performing dotprod on GPU
Done in 1.00ms
Total time taken - 24.50ms (includes kernel launch and result retreival)
*** verify that all 3 ops produce the same result ***
cpu: [391, 0, 35, 116, 810], [48, 155, 126, 48, 0]
cpu_par: [391, 0, 35, 116, 810], [48, 155, 126, 48, 0]
gpu: [391, 0, 35, 116, 810], [48, 155, 126, 48, 0]
____*** vector dotprod of 1,000,000 elements of type `f16` ***___
Dotprod on CPU
Done in 18.75ms
Dotprod on CPU - parallel
Done in 3.37ms
Dotprod on GPU
Actual time spent performing dotprod on GPU
Done in 869.25µs
Total time taken - 2.25ms (includes kernel launch and result retreival) # interesting, looks like metal reuses most objects or resources instantiated from the previous dispatch call (i.e. device, queue etc.).
*** verify that all 3 ops produce the same result ***
cpu: [0.72802734, 0.0037574768, 0.0947876, 0.16601563, 0.26367188], [0.31933594, 0.2919922, 0.12042236, 0.20458984, 0.30151367]
cpu_par: [0.72802734, 0.0037574768, 0.0947876, 0.16601563, 0.26367188], [0.31933594, 0.2919922, 0.12042236, 0.20458984, 0.30151367]
gpu: [0.72802734, 0.0037574768, 0.0947876, 0.16601563, 0.26367188], [0.31933594, 0.2919922, 0.12042236, 0.20458984, 0.30151367]