Developer Guide and Reference

ID 767251
Date 10/31/2024
Public
Document Table of Contents

Ahead of Time Compilation

Ahead of Time (AOT) Compilation is a helpful feature for your development lifecycle or distribution time. The AOT feature provides the following benefits when you know beforehand what your target device is going to be at application execution time:

  • No additional compilation time is done when running your application.

  • No just-in-time (JIT) bugs encountered due to compilation for the target. Any bugs should be found during AOT and resolved.

  • Your final code, executing on the target device, can be tested as-is before you deliver it to end-users.

A program built with AOT compilation for specific target device(s) will not run on different device(s). You must detect the proper target device at runtime and report an error if the targeted device is not present. The use of exception handling with an asynchronous exception handler is recommended.

SYCL supports AOT compilation for the following targets: Intel® CPUs, Intel® Processor Graphics, and Intel® FPGA. For details on AOT compilation for Intel FPGAs, refer to the Intel® oneAPI FPGA Handbook.

OpenMP supports AOT compilation for the following targets: Intel® Processor Graphics.

For additional information, watch two videos for a quick overview on how to apply the JIT and AOT compilation options:

Prerequisites

To target a GPU with the AOT feature, you must have the OpenCL™ Offline Compiler (OCLOC) tool installed. OCLOC can generate binaries that use OpenCL™ (SYCL only) or the Intel® oneAPI Level Zero (Level Zero) backend.

OCLOC is not packaged with the compiler and must be installed separately. To install OCLOC, you need to install the GPU drivers (whether or not you have an Intel GPU on your system). Refer to the Installing GPU drivers for instructions.

Requirements for Accelerators

GPUs:

  • Intel® UDH Graphics for 11th generation Intel processors or newer

  • Intel® Iris® Xe graphics

  • Intel® Arc™ graphics

  • Intel® Data Center GPU Flex Series

  • Intel® Data Center GPU Max Series

AOT Compilation Supported Options for OpenMP

Use the following options to target a specific device for AOT compilation for OpenMP:

  • -fopenmp-target to specify the device target

  • -Xopenmp-target-backend to pass options to the backend tool

Option -Xopenmp-target-backend is a general device target option. If multiple targets are desired (for example: -fopenmp-targets=spir64,spir64_gen), the options specified with -Xopenmp-target-backend apply to all targets.

For multiple targets, you can add specificity by using, for example, Xopenmp-target-backend=spir64_gen <option>.

When using Ahead of Time (AOT) compilation, the options passed with -Xopenmp-target-backend are not compiler options, but rather options to pass to OCLOC.

To see a list of the options you can pass with -Xopenmp-target-backend when using AOT, specify -fsycl-help=gen on the command line.

AOT Compilation Supported Options for SYCL

Use the following options to target a specific device for AOT compilation for SYCL:

  • -fsycl-target to specify the device target

  • -Xsycl-target-backend to pass options to the backend tool

Option -Xsycl-target-backend is a general device target option. If multiple targets are desired (for example: -fopenmp-targets=spir64,spir64_gen), the options specified with -Xsycl-target-backend apply to all targets.

For multiple targets, you can add specificity by using, for example, Xsycl-target-backend=spir64_gen <option>.

When using Ahead of Time (AOT) compilation, the options passed with -Xsycl-target-backend are not compiler options.

To see a list of the options you can pass with -Xsycl-target-backend when using AOT, specify -fsycl-help=gen on the command line.

Use AOT for the Target Device (Intel® CPUs)

NOTE:

SYCL compilation is only available with the C/C++ compiler.

However, you can link SYCL-generated objects with the Fortran compiler. The use of -fsycl with ifx allows this, though it is restricted to spir64, spir64_gen, and spir64_x86_64).

Use the following option argument to specify Intel® CPUs as the target device for AOT compilation:

  • -fsycl-targets=spir64_x86_64

The following examples tell the compiler to generate code that uses Intel® AVX2 instructions:

Linux

ifx -fsycl -fsycl-targets=spir64_x86_64 -Xsycl-target-backend "-march=avx2" main.o 

Windows

ifx -fsycl -fsycl-targets=spir64_x86_64 -Xsycl-target-backend=spir64_x86_64 "-march=avx2" main.obj 

Build an Application with Multiple Source Files for CPU Targeting

NOTE:
This section is for SYCL only.

Compile your normal files (with no SYCL kernels) to create host objects. Then compile the file with the kernel code and link it with the rest of the application.

Linux

The following shows an example of C/C++ Linux* compilation code:

icpx -c main.cpp      // This creates the host object that is used below.
icpx -c -fsycl-targets=spir64_x86_64 -Xsycl-target-backend "-march=mavx2" mandel.cpp

For C/C++, this would be the next step:

icpx -fsycl-targets=spir64_x86_64 -Xsycl-target-backend "-march=mavx2" mandel.o main.o

Note that Fortran can use the -c compiled variant as follows:

ifx -fsycl -fsycl-targets=spir64_x86_64 -Xsycl-target-backend "-march=mavx2" mandel.o main.o

Windows

The following shows an example of C/C++ Windows* compilation code:

icx /EHsc -c main.cpp
icx /EHsc -c -fsycl-targets=spir64_x86_64 -Xsycl-target-backend "-march=mavx2" mandel.cpp

For C/C++, this would be the next step:

icx -fsycl-targets=spir64_x86_64 -Xsycl-target-backend "-march=mavx2" mandel.obj main.obj

Note that Fortran can use the -c compiled variant as follows:

ifx -fsycl -fsycl-targets=spir64_x86_64 -Xsycl-target-backend "-march=mavx2" mandel.obj main.obj

Use AOT for Integrated Graphics (Intel® GPU)

Use the following option arguments to specify Intel® GPU as the target device for AOT compilation:

OpenMP

Option -Xopenmp-target-backend is a general-purpose option, any arguments supplied with -Xopenmp-target-backend will be applied to all offline compilation invocations. These are the relevant options and arguments:

  • -Xopenmp-target-backend "-device <arch>", where <arch> is the target device

  • -fopenmp-targets=spir64_gen

  • -fopenmp-device-code-split=<value> to perform an OpenMP device code split. The <value> is:

    • per_kernel, which creates a device code module for each OpenMP kernel

SYCL

Option -Xsycl-target-backend is a general-purpose option, any arguments supplied with -Xsycl-target-backend will be applied to all offline compilation invocations. These are the relevant options and arguments:

  • -Xsycl-target-backend "-device <arch>", where <arch> is the target device

  • -fsycl-targets=spir64_gen

  • -fsycl-device-code-split=<value> option to perform SYCL device code split. The <value> can be:

    • per_kernel, which creates a device code module for each SYCL kernel

    • per_source, which creates a device code module for each source (translation unit)

    • off, which disables device code split

    • auto, which tells the compiler to use a heuristic to select the best way of splitting device code

      This is the default, and it is the same as specifying -fsycl-device-code-split with no <value>.

To see the complete list of supported target device types for your installed version of OCLOC, run:

ocloc compile --help

To find supported devices look for -device <device_type> in the online help.

If multiple target devices are listed in the compile command, the compiler will compile for each of these targets and create a fat-binary that contains all the device binaries produced this way.

Examples of supported -device patterns:

OpenMP for Linux

  • To compile for a single target, using skl as an example, use:
    ifx -fiopenmp -fopenmp-targets=spir64_gen -Xopenmp-target-backend "-device skl" vector-add.f90
  • To compile for two targets, using skl and icllp as examples, use:
    ifx -fiopenmp -fopenmp-targets=spir64_gen -Xopenmp-target-backend "-device skl,icllp" vector-add.f90
  • To compile for all the targets known to OCLOC, use:
    ifx -fiopenmp -fopenmp-targets=spir64_gen -Xopenmp-target-backend=spir64_gen "-device *" vector-add.f90

SYCL for Linux

Consider the following C/C++ command:

icpx -fsycl -fsycl-targets=spir64_gen -Xsycl-target-backend "-device *" vector-add.cpp

If vector-add.cpp is compiled with option -c to create vector-add.obj, then Fortran can use this SYCL-based fat object with the following command:

ifx -fsycl -fsycl-targets=spir64_gen -Xsycl-target-backend "-device *" vector-add.obj

SYCL for Windows

Consider the following C/C++ command:

icpx -fsycl -fsycl-targets=spir64_gen -Xsycl-target-backend "-device *" vector-add.cpp

If vector-add.cpp is compiled with option -c to create vector-add.obj, then Fortran can use this SYCL-based fat object with the following command:

ifx -fsycl -fsycl-targets=spir64_gen -Xsycl-target-backend "-device *" vector-add.obj

Build an Application with Multiple Source Files for GPU Targeting

Compile your normal files (with no SYCL kernels) to create host objects. Then compile the file with the kernel code and link it with the rest of the application.

Linux

Consider the following C/C++ command:

icpx -fsycl -fsycl-targets=spir64_gen -Xsycl-target-backend=spir64_gen "-device *" mandel.cpp main.o

Assuming that mandel.o has been built by the C/C++ compiler, Fortran can use this SYCL-based fat object with the following command:

ifx -fsycl -fsycl-targets=spir64_gen -Xsycl-target-backend=spir64_gen "-device *" main.o mandel.o 

Windows

Consider the following C/C++ command:

icx -fsycl /EHsc -fsycl-targets=spir64_gen -Xsycl-target-backend=spir64_gen "-device *" -c mandel.cpp

Assuming that mandel.o has been built by the C/C++ compiler, Fortran can use this SYCL-based fat object with the following command:

ifx -fsycl -fsycl-targets=spir64_gen -Xsycl-target-backend=spir64_gen "-device *" mandel.obj main.obj

Available GPU Platforms

GPU Model Name Vertical Segment Product Code Name AOT Compilation Device Name Compatible Targets

Intel® Arc™ graphics 140V (Integrated in Intel® Core™ Ultra 9 Processor 288V, Intel® Core™ Ultra 7 Processor 268V, Intel® Core™ Ultra 7 Processor 266V, Intel® Core™ Ultra 7 Processor 258V, Intel® Core™ Ultra 7 Processor 256V)

Mobile

Lunar Lake

lnl-m

 

Intel® Arc™ graphics 130V (Integrated in Intel® Core™ Ultra 5 Processor 238V, Intel® Core™ Ultra 5 Processor 236V, Intel® Core™ Ultra 5 Processor 228V, Intel® Core™ Ultra 5 Processor 226V)

Mobile

Lunar Lake

lnl-m

 

Intel® Arc™ graphics (Integrated in Intel® Core™ Ultra 9 Processor 185H, Intel® Core™ Ultra 7 Processor 165H, Intel® Core™ Ultra 7 Processor 155H, Intel® Core™ Ultra 5 Processor 135H, Intel® Core™ Ultra 5 Processor 125H)

Mobile

Meteor Lake-H

mtl-h

mtl

Intel® Arc™ graphics (Integrated in Intel® Core™ Ultra 7 Processor 165HL, Intel® Core™ Ultra 7 Processor 155HL, Intel® Core™ Ultra 5 Processor 135HL, Intel® Core™ Ultra 5 Processor 125HL)

Embedded

Meteor Lake-H

mtl-h

mtl

Intel® Graphics (Integrated in Intel® Core™ Ultra 7 Processor 165U, Intel® Core™ Ultra 7 Processor 164U, Intel® Core™ Ultra 7 Processor 155U, Intel® Core™ Ultra 5 Processor 135U, Intel® Core™ Ultra 5 Processor 134U, Intel® Core™ Ultra 5 Processor 125U)

Mobile

Meteor Lake-U, Arrow Lake-U/S

mtl-u (or arl-u, arl-s)

mtl

Intel® Graphics (Integrated in Intel® Core™ Ultra 7 Processor 165UL, Intel® Core™ Ultra 7 Processor 155UL, Intel® Core™ Ultra 5 Processor 135UL, Intel® Core™ Ultra 5 Processor 125UL, Intel® Core™ Ultra 3 Processor 105UL)

Embedded

Meteor Lake-U, Arrow Lake-U/S

mtl-u (or arl-u, arl-s)

mtl

Intel® MAX® 1550, Intel® MAX® 1100

Data Center

Ponte Vecchio

pvc

 

Intel® Flex 170

Data Center

Arctic Sound

ats-m150

dg2

Intel® Flex 140

Data Center

Arctic Sound

ats-m75

dg2

Intel® Arc™ A770, Intel® Arc™ A750, Intel® Arc™ A580

Desktop

Alchemist

acm-g10 (or dg2-g10, ats-m150)

dg2

Intel® Arc™ A770M, Intel® Arc™ A730M, Intel® Arc™ A550M

Mobile

Alchemist

acm-g10 (or dg2-g10, ats-m150)

dg2

Intel® Arc™ A380, Intel® Arc™ A310, Intel® Arc™ Pro A40/A50

Desktop

Alchemist

acm-g11 (or dg2-g11, ats-m75)

dg2

Intel® Arc™ A370M, Intel® Arc™ A350M, Intel® Arc™ Pro A30M

Mobile

Alchemist

acm-g11 (or dg2-g11, ats-m75)

dg2

Intel® Arc™ A380E, Intel® Arc™ A370E, Arc™ A350E, Intel® Arc™ A310E

Embedded

Alchemist

acm-g11 (or dg2-g11, ats-m75)

dg2

Intel® UHD Graphics

Mobile

Alder Lake-N

adl-n

 

Intel® UHD Graphics, Intel® Iris® Xe graphics

Mobile

Alder Lake-P

adl-p

 

Intel® UHD Graphics 770/730/710

Mobile

Alder Lake-S

adl-s

 

Intel® UHD Graphics 617/615

Mobile

Amber Lake

aml

 

Intel® HD Graphics, Intel® HD Graphics 505/500

Mobile

Apollo Lake, Broxton

apl (or bxt)

 

Intel® Iris® Plus graphics 655/645, Intel® UHD Graphics 630/610/P630

Mobile

Coffee Lake

cfl

 

Intel® UHD Graphics

Mobile

Comet Lake

cml

 

Intel® Iris® Xe MAX graphics, Intel® Iris® Xe graphics, Intel® Iris® Xe MAX 100, Intel® Server GPU SG-18M

Mobile/Server

DG1

dg1

 

Intel® UHD Graphics

Mobile

Elkhart Lake, Jasper Lake

ehl jsl

 

Intel® UHD Graphics 605/600

Mobile

Gemini Lake

glk

 

Intel® HD Graphics, Intel® UHD Graphics, Intel® Iris® Plus Graphics

Mobile

Ice Lake

icllp

 

Intel® HD Graphics 635, Intel® Iris® Plus Graphics 650/640, Intel® HD Graphics 630/620/P630/615/610, Intel® UHD Graphics 617/615

Mobile

Kaby Lake

kbl

 

Intel® UHD Graphics 750/730/P750

Mobile

Rocket Lake

rkl

 

Intel® Iris® Xe Graphics, Intel® UHD Graphics

Mobile

Raptor Lake-P

rpl-p

 

Intel® UHD Graphics 770/730/710

Mobile

Raptor Lake-S

rpl-s

 

Intel® HD Graphics 535/530/520/515/510/P530, Intel® Iris® Pro Graphics 580/P580, Intel® Iris® Graphics 555/550/540/P555

Mobile

Intel® microarchitecture code name Skylake

skl

 

Intel® UHD Graphics, Intel® Iris® Xe Graphics

Mobile

Tiger Lake

tgllp

 

Intel® UHD Graphics, Intel® UHD Graphics 620

Mobile

Whiskey Lake

whl

 

See Also