Metal support for Swift #3078

kchro3 · 2023-09-08T05:41:01Z

I have a working demo of using Metal w/ a Swift Mac app with these changes. Hopefully, this is a welcome contribution!

llama_model_loader: loaded meta data with 19 key-value pairs and 363 tensors from /Users/jeffhara/.cache/lm-studio/models/TheBloke/MythoMax-L2-Kimiko-v2-13B-GGUF/mythomax-l2-kimiko-v2-13b.Q4_K_M.gguf (version GGUF V2 (latest))
llama_model_loader: - tensor    0:                token_embd.weight q4_K     [  5120, 32000,     1,     1 ]
...B (+  400.00 MB per state)
...................................................................................................
llama_new_context_with_model: kv self size  =  400.00 MB
ggml_metal_init: allocating
2023-09-07 22:35:08.973604-0700 TestTypeaheadAI[60657:1063549] Metal GPU Frame Capture Enabled
2023-09-07 22:35:08.973931-0700 TestTypeaheadAI[60657:1063549] Metal API Validation Enabled
ggml_metal_init: found device: Apple M1 Pro
ggml_metal_init: picking default device: Apple M1 Pro
ggml_metal_init: loaded kernel_add                         0x600000fd0370 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_add_row                     0x600000fd0500 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul                         0x600000fd0690 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_row                     0x600000fd0820 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_scale                       0x600000fd44b0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_silu                        0x600000fd4640 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_relu                        0x600000fd47d0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_gelu                        0x600000fee7b0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_soft_max                    0x600000fee940 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_diag_mask_inf               0x600000feead0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_f16                0x600000feec60 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q4_0               0x600000feedf0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q4_1               0x600000feef80 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q8_0               0x600000fd09b0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q2_K               0x600000fd0b40 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q3_K               0x600000fd0cd0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q4_K               0x600000fd0e60 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q5_K               0x600000fd0ff0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q6_K               0x600000fd1180 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_rms_norm                    0x600000fd1310 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_norm                        0x600000fd14a0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mat_f16_f32             0x600000fd1630 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mat_q4_0_f32            0x600000fd17c0 | th_max =  896 | th_width =   32
ggml_metal_init: loaded kernel_mul_mat_q4_1_f32            0x600000fd1950 | th_max =  896 | th_width =   32
ggml_metal_init: loaded kernel_mul_mat_q8_0_f32            0x600000fd1ae0 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mat_q2_K_f32            0x600000fd1c70 | th_max =  640 | th_width =   32
ggml_metal_init: loaded kernel_mul_mat_q3_K_f32            0x600000fd1e00 | th_max =  704 | th_width =   32
ggml_metal_init: loaded kernel_mul_mat_q4_K_f32            0x600000fd1f90 | th_max =  576 | th_width =   32
ggml_metal_init: loaded kernel_mul_mat_q5_K_f32            0x600000fd2120 | th_max =  576 | th_width =   32
ggml_metal_init: loaded kernel_mul_mat_q6_K_f32            0x600000fd22b0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_f16_f32              0x600000fd2440 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q4_0_f32             0x600000fd25d0 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q8_0_f32             0x600000fd2760 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q4_1_f32             0x600000fd28f0 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q2_K_f32             0x600000fd2a80 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q3_K_f32             0x600000fd2c10 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q4_K_f32             0x600000fd2da0 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q5_K_f32             0x600000fd2f30 | th_max =  704 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q6_K_f32             0x600000fd30c0 | th_max =  704 | th_width =   32
ggml_metal_init: loaded kernel_rope                        0x600000fd3250 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_alibi_f32                   0x600000fd33e0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_cpy_f32_f16                 0x600000fd3610 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_cpy_f32_f32                 0x600000fd37a0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_cpy_f16_f16                 0x600000fd3930 | th_max = 1024 | th_width =   32
ggml_metal_init: recommendedMaxWorkingSetSize  = 10922.67 MB
ggml_metal_init: hasUnifiedMemory              = true
ggml_metal_init: maxTransferRate               = built-in GPU
llama_new_context_with_model: compute buffer total size =   91.47 MB
llama_new_context_with_model: max tensor size =   128.17 MB
ggml_metal_add_buffer: allocated 'data            ' buffer, size =  7501.56 MB, ( 7502.12 / 10922.67)
ggml_metal_add_buffer: allocated 'eval            ' buffer, size =     1.48 MB, ( 7503.61 / 10922.67)
ggml_metal_add_buffer: allocated 'kv              ' buffer, size =   402.00 MB, ( 7905.61 / 10922.67)
ggml_metal_add_buffer: allocated 'alloc           ' buffer, size =    90.02 MB, ( 7995.62 / 10922.67)


 what is the capital of japan
The capital of Japan is Tokyo. [end of text]
0
ggml_metal_free: deallocating

kchro3 · 2023-09-08T05:43:01Z

ggml-metal.m

@@ -140,12 +140,22 @@ @implementation GGMLMetalClass

    ctx->d_queue = dispatch_queue_create("llama.cpp", DISPATCH_QUEUE_CONCURRENT);

-#if 0


Thought it would be ok to replace this since it looked unfinished.

pkrmf · 2023-09-08T13:30:58Z

Package.swift

            ],
            publicHeadersPath: "spm-headers",
            cSettings: [
                .unsafeFlags(["-Wno-shorten-64-to-32"]),
+                .unsafeFlags(["-fno-objc-arc"]),
+                .define("GGML_SWIFT"),
+                .define("GGML_USE_METAL"),


Isn't this change forcing everyone to use metal? Can this be a flag defined by the customer instead? For instance, I can't run llamacpp with metal ON with my old MacBook and an AMD card

@kchro3 Let's address this comment and we can merge

how does it look now? i don't have an old macbook, but i was able to build it if i switched the if/else condition

# in Package.swift #if arch(x86_64) // instead of arch(arm) || arch(arm64)

// demo that it's not using metal anymore llm_load_tensors: ggml ctx size = 0.12 MB llm_load_tensors: mem required = 7500.97 MB (+ 400.00 MB per state) ................................................................................................... llama_new_context_with_model: kv self size = 400.00 MB llama_new_context_with_model: compute buffer total size = 75.47 MB what is the capital of japanToken received in Swift: Token received in Swift: The Token received in Swift: capital

pkrmf · 2023-09-08T16:23:16Z

Package.swift

@@ -4,23 +4,27 @@ import PackageDescription

 let package = Package(
    name: "llama",
+    platforms: [.macOS(.v11)],


I haven't tried iOS but I do wonder if we are OK by limiting this package to macOS only. Can llamacpp run on iOS, tvOS or even watchOS @ggerganov?

It can run even on a refrigerator 😄

Jokes aside - I see no reason to limit this to just macOS

i'm not sure why, but the compiler was not happy if platforms was not included, although that could be a metal thing?

i don't have a way to test on watchOS or tvOS... i can set it to the minimum non-deprecated version and if someone tries to cross that bridge, we could update it?

do you mind sharing the compiler error?

Hey folks, I would appreciate help on this. I'm seeing in my build logs that it's compiling the .metal file even if I put it in resources.

For example, if I do:

#if arch(arm) || arch(arm64) let platforms: [SupportedPlatform]? = [ .macOS(.v11), .iOS(.v11), .watchOS(.v4), .tvOS(.v11) ] let exclude: [String] = [] let resources: [Resource]? = [ .copy("ggml-metal.metal"), .copy("README.md") // just to validate that files get copied ] let additionalSources: [String] = ["ggml-metal.m"] let additionalSettings: [CSetting] = [ .unsafeFlags(["-fno-objc-arc"]), .define("GGML_SWIFT"), .define("GGML_USE_METAL") ] #else

I still see the default.metallib in my resources:

ls /Users/.../Library/Developer/Xcode/DerivedData/.../Build/Products/Debug/....app/Contents/Resources/llama_llama.bundle/Contents/Resources/ README.md default.metallib

~~Could it be because the file is in the project root and the target path is "."?~~ tried copying it into a new directory & excluding the original, but it still compiled...

what if you exclude ggml-metal.metal like it is done in master right now, but then add it in the resources section. That should do it I think

https://developer.apple.com/documentation/packagedescription/target/exclude#discussion

I think it doesn't work because exclude takes precedence over resources. For example, I pushed a branch https://github.com/ggerganov/llama.cpp/pull/3091/files, and my build logs don't show the .metal file:

https://developer.apple.com/library/archive/documentation/3DDrawing/Conceptual/MTLBestPracticesGuide/FunctionsandLibraries.html

Just a sanity check, but this documentation is saying that .metal files get automatically compiled, and that seems to be the case from what I've tried. Is there a specific reason why we need to compile from source?

https://developer.apple.com/library/archive/documentation/3DDrawing/Conceptual/MTLBestPracticesGuide/FunctionsandLibraries.html

Just a sanity check, but this documentation is saying that .metal files get automatically compiled, and that seems to be the case from what I've tried.

Got it, it looks like a better way if we use it on Xcode.

kchro3 · 2023-09-09T05:32:55Z

cc: @ggerganov, i think that all comments are now addressed

jhen0409 · 2023-09-09T06:42:56Z

After I give a try in a new Xcode app project, figured out the reason of the ggml-metal.metal compile errors on iOS:

Required iOS / tvOS 14.0 to use int64_t in Metal (ref)
Required Metal >= v2.3 ~~(Define MTL_LANGUAGE_REVISION = Metal23) (ref: search simd_sum)~~ (Not necessary)

Also, Metal may not be available on watchOS.

Package.swift

Co-authored-by: Jhen-Jie Hong <iainst0409@gmail.com>

ggerganov

@jhen0409
Can't give this a test atm - if all works merge it

kchro3 commented Sep 8, 2023

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kchro3 added 2 commits September 8, 2023 01:58

Metal support for Swift

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update

ce92d75

kchro3 force-pushed the kchro3/llama-swift-metal-support branch from 615b02c to ce92d75 Compare September 8, 2023 08:58

pkrmf reviewed Sep 8, 2023

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kchro3 added 2 commits September 8, 2023 09:26

add a toggle for arm/arm64

99f85e7

set minimum versions for all platforms

690c794

jhen0409 mentioned this pull request Sep 8, 2023

metal : support build for iOS/tvOS #3089

Merged

update to use newLibraryWithURL

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jhen0409 reviewed Sep 9, 2023

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bump version

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Co-authored-by: Jhen-Jie Hong <iainst0409@gmail.com>

ggerganov approved these changes Sep 9, 2023

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jhen0409 merged commit 21ac3a1 into ggerganov:master Sep 9, 2023
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kchro3 mentioned this pull request Dec 5, 2023

Revert compiler checks for swift package #4332

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Metal support for Swift #3078

Metal support for Swift #3078

kchro3 commented Sep 8, 2023

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		@@ -140,12 +140,22 @@ @implementation GGMLMetalClass

		ctx->d_queue = dispatch_queue_create("llama.cpp", DISPATCH_QUEUE_CONCURRENT);

		#if 0

Metal support for Swift #3078

Metal support for Swift #3078

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