Apple M1, M2, M3, M4

[Artoria2e5]

OpenMM has had support for using OpenCL with Apple M1 since circa 2022. It would make sense for people currently crunching on their Apple Silicon machines to also use the GPU part of the chip.

While OpenCL deprecation is a concern, the API still works. According to https://github.com/openmm/openmm/issues/2489 the OpenMM people currently sees no reason to add a metal platform to the main codebase so long as OpenCL is working.

There is an unofficial metal platform plugin which runs faster, but it's unmaintained and is (again) not necessary for OpenMM to work on macOS. So my recommendation is to just ship ARM64+OpenCL versions of these cores.

FWIW, my clinfo:

Code: Select all

Number of platforms                               1
  Platform Name                                   Apple
  Platform Vendor                                 Apple
  Platform Version                                OpenCL 1.2 (Dec 13 2024 23:09:21)
  Platform Profile                                FULL_PROFILE
  Platform Extensions                             cl_APPLE_SetMemObjectDestructor cl_APPLE_ContextLoggingFunctions cl_APPLE_clut cl_APPLE_query_kernel_names cl_APPLE_gl_sharing cl_khr_gl_event

  Platform Name                                   Apple
Number of devices                                 1
  Device Name                                     Apple M4
  Device Vendor                                   Apple
  Device Vendor ID                                0x1027f00
  Device Version                                  OpenCL 1.2
  Driver Version                                  1.2 1.0
  Device OpenCL C Version                         OpenCL C 1.2
  Device Type                                     GPU
  Device Profile                                  FULL_PROFILE
  Device Available                                Yes
  Compiler Available                              Yes
  Linker Available                                Yes
  Max compute units                               10
  Max clock frequency                             1000MHz
  Device Partition                                (core)
    Max number of sub-devices                     0
    Supported partition types                     None
    Supported affinity domains                    (n/a)
  Max work item dimensions                        3
  Max work item sizes                             256x256x256
  Max work group size                             256
  Preferred work group size multiple (kernel)     32
  Preferred / native vector sizes
    char                                                 1 / 1
    short                                                1 / 1
    int                                                  1 / 1
    long                                                 1 / 1
    half                                                 0 / 0        (n/a)
    float                                                1 / 1
    double                                               1 / 1        (n/a)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     No
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               Yes
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  Yes
  Double-precision Floating-point support         (n/a)
  Address bits                                    64, Little-Endian
  Global memory size                              11453251584 (10.67GiB)
  Error Correction support                        No
  Max memory allocation                           2147483648 (2GiB)
  Unified memory for Host and Device              Yes
  Minimum alignment for any data type             1 bytes
  Alignment of base address                       32768 bits (4096 bytes)
  Global Memory cache type                        None
  Image support                                   Yes
    Max number of samplers per kernel             32
    Max size for 1D images from buffer            268435456 pixels
    Max 1D or 2D image array size                 2048 images
    Base address alignment for 2D image buffers   256 bytes
    Pitch alignment for 2D image buffers          256 pixels
    Max 2D image size                             16384x16384 pixels
    Max 3D image size                             2048x2048x2048 pixels
    Max number of read image args                 128
    Max number of write image args                8
  Local memory type                               Local
  Local memory size                               32768 (32KiB)
  Max number of constant args                     31
  Max constant buffer size                        1073741824 (1024MiB)
  Max size of kernel argument                     4096 (4KiB)
  Queue properties
    Out-of-order execution                        No
    Profiling                                     Yes
  Prefer user sync for interop                    Yes
  Profiling timer resolution                      1000ns
  Execution capabilities
    Run OpenCL kernels                            Yes
    Run native kernels                            No
  printf() buffer size                            1048576 (1024KiB)
  Built-in kernels                                (n/a)
  Device Extensions                               cl_APPLE_SetMemObjectDestructor cl_APPLE_ContextLoggingFunctions cl_APPLE_clut cl_APPLE_query_kernel_names cl_APPLE_gl_sharing cl_khr_gl_event cl_khr_byte_addressable_store cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_3d_image_writes cl_khr_image2d_from_buffer cl_khr_depth_images

NULL platform behavior
  clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...)  Apple
  clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...)   Success [P0]
  clCreateContext(NULL, ...) [default]            Success [P0]
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT)  Success (1)
    Platform Name                                 Apple
    Device Name                                   Apple M4
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU)  Success (1)
    Platform Name                                 Apple
    Device Name                                   Apple M4
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM)  Invalid device type for platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL)  Success (1)
    Platform Name                                 Apple
    Device Name                                   Apple M4

[Joe_H]

Yes, OpenCL is available, but so far there have been no plans to develop a GPU folding core for the macOS to do GPU folding. Among other issues besides concerns over the deprecated status of OpenCL is that the current methods used by the folding client to detect a GPU do not work. The GPU section of the M-series processors do not show up as a PCI device. So to support macOS GPU folding non the M-series chips would require writing entirely new code for the F@h client.

One other concern I see from the clinfo report is that it lists no support for Double-precision Floating-point. Currently all GPU folding cores for F@H enable that and use it for some critical calculations during WU processing. I don't know if that is an actual limitation of the M-series GPU sections or a failing of clinfo.