Intel® oneAPI DPC++/C++ Compiler Developer Guide and Reference

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Date 9/08/2022
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Document Table of Contents
Document Table of Contents x
Intel® oneAPI DPC++/C++ Compiler Developer Guide and Reference
Intel® oneAPI DPC++/C++ Compiler Developer Guide and Reference x
Intel® oneAPI DPC++/C++ Compiler Introduction Compiler Setup Compiler Reference Compilation Optimization and Programming Compatibility and Portability Notices and Disclaimers
Intel® oneAPI DPC++/C++ Compiler Introduction x
Get Help and Support Related Information
Compiler Setup x
Use the Command Line Use Eclipse Use Microsoft Visual Studio
Use the Command Line x
Specify Component Locations Invoke the Compiler Use the Command Line on Windows File Extensions Use Makefiles for Compilation Use CMake with the Compiler Use Compiler Options Specify Compiler Files Convert Projects to Use a Selected Compiler
Use Eclipse x
Add the Compiler to Eclipse Multiversion Compiler Support Use Cheat Sheets Create a Simple Eclipse Project Makefiles Use Intel Libraries with Eclipse
Use Microsoft Visual Studio x
Create a New Project Use the Intel® oneAPI DPC++/C++ Compiler Select the Compiler Version Specify a Base Platform Toolset Use Property Pages Use Intel® Libraries with Microsoft Visual Studio* Include MPI Support Dialog Box Help
Dialog Box Help x
Options: Compilers dialog box Use Intel® oneAPI DPC++/C++ Compiler dialog box Options: Intel Libraries for oneAPI dialog box Options: Converter dialog box
Compiler Reference x
C/C++/SYCL Calling Conventions Compiler Options Floating-Point Operations Attributes Intrinsics Libraries Macros Pragmas Error Handling
Compiler Options x
Alphabetical Option List General Rules for Compiler Options What Appears in the Compiler Option Descriptions Optimization Options Code Generation Options Interprocedural Optimization Options Advanced Optimization Options Optimization Report Options Offload Compilation, OpenMP*, and Parallel Processing Options Floating-Point Options Inlining Options Output, Debug, and Precompiled Header Options Preprocessor Options Component Control Options Language Options Data Options Compiler Diagnostic Options Compatibility Options Linking or Linker Options Miscellaneous Options Deprecated and Removed Compiler Options Display Option Information Alternate Compiler Options Portability and GCC-compatible Warning Options
Optimization Options x
fast fbuiltin, Oi foptimize-sibling-calls GF nolib-inline O Od Ofast Os Ot Ox
Code Generation Options x
arch ax, Qax EH fasynchronous-unwind-tables fdata-sections, Gw fexceptions ffunction-sections, Gy fomit-frame-pointer Gd GR guard Gv m, Qm m64, Qm64 m80387 march masm mbranches-within-32B-boundaries, Qbranches-within-32B-boundaries mintrinsic-promote, Qintrinsic-promote momit-leaf-frame-pointer mtune, tune regcall, Qregcall x, Qx xHost, QxHost
Interprocedural Optimization Options x
flto ipo, Qipo
Advanced Optimization Options x
ffreestanding, Qfreestanding fjump-tables fvec-peel-loops, Qvec-peel-loops fvec-remainder-loops, Qvec-remainder-loops fvec-with-mask, Qvec-with-mask ipp-link, Qipp-link qactypes, Qactypes qdaal, Qdaal qipp, Qipp qmkl, Qmkl qmkl-ilp64, Qmkl-ilp64 qopt-assume-no-loop-carried-dep, Qopt-assume-no-loop-carried-dep qopt-dynamic-align, Qopt-dynamic-align qopt-for-throughput, Qopt-for-throughput qopt-multiple-gather-scatter-by-shuffles, Qopt-multiple-gather-scatter-by-shuffles qopt-streaming-stores, Qopt-streaming-stores qtbb, Qtbb unroll, Qunroll use-intel-optimized-headers, Quse-intel-optimized-headers vec, Qvec vec-threshold, Qvec-threshold
Optimization Report Options x
qopt-report, Qopt-report qopt-report-file, Qopt-report-file
Offload Compilation, OpenMP*, and Parallel Processing Options x
device-math-lib fintelfpga fiopenmp, Qiopenmp fno-sycl-libspirv foffload-static-lib fopenmp fopenmp-declare-target-scalar-defaultmap, Qopenmp-declare-target-scalar-defaultmap fopenmp-device-lib fopenmp-target-buffers, Qopenmp-target-buffers fopenmp-targets, Qopenmp-targets fsycl fsycl-add-targets fsycl-dead-args-optimization fsycl-device-code-split fsycl-device-lib fsycl-device-only fsycl-early-optimizations fsycl-enable-function-pointers fsycl-esimd-force-stateless-mem fsycl-explicit-simd fsycl-force-target fsycl-help fsycl-host-compiler fsycl-host-compiler-options fsycl-id-queries-fit-in-int fsycl-instrument-device-code fsycl-link fsycl-link-huge-device-code fsycl-link-targets fsycl-max-parallel-link-jobs fsycl-targets fsycl-unnamed-lambda fsycl-use-bitcode nolibsycl qopenmp, Qopenmp qopenmp-lib, Qopenmp-lib qopenmp-link qopenmp-simd, Qopenmp-simd qopenmp-stubs, Qopenmp-stubs reuse-exe Wno-sycl-strict Xopenmp-target Xs Xsycl-target
Floating-Point Options x
ffp-contract fimf-absolute-error, Qimf-absolute-error fimf-accuracy-bits, Qimf-accuracy-bits fimf-arch-consistency, Qimf-arch-consistency fimf-domain-exclusion, Qimf-domain-exclusion fimf-force-dynamic-target, Qimf-force-dynamic-target fimf-max-error, Qimf-max-error fimf-precision, Qimf-precision fimf-use-svml, Qimf-use-svml fma, Qfma fp-model, fp fp-speculation, Qfp-speculation pc, Qpc
Inlining Options x
fgnu89-inline finline finline-functions
Output, Debug, and Precompiled Header Options x
c debug (Linux*) debug (Windows*) Fa fasm-blocks FD Fe Fo Fp ftrapuv, Qtrapuv fverbose-asm g gdwarf grecord-gcc-switches gsplit-dwarf o RTC S use-msasm Y- Yc Yu Zi, Z7, ZI
Preprocessor Options x
B C D dD, QdD dM, QdM E EP FI H, QH I I- idirafter imacros iprefix iquote isystem iwithprefix iwithprefixbefore Kc++, TP M, QM MD, QMD MF, QMF MG, QMG MM, QMM MMD, QMMD MQ MT, QMT nostdinc++ P pragma-optimization-level U undef X
Component Control Options x
Qoption
Language Options x
ansi fno-gnu-keywords fno-operator-names fno-rtti fpermissive fshort-enums fsyntax-only funsigned-char J std, Qstd strict-ansi vd vmg x (type option) Zc Zg Zp Zs
Data Options x
fcommon fkeep-static-consts, Qkeep-static-consts fmath-errno fpack-struct fpic fpie fstack-protector fstack-security-check fvisibility fzero-initialized-in-bss, Qzero-initialized-in-bss GA Gs GS mcmodel Qlong-double
Compiler Diagnostic Options x
w w, W Wabi Wall Wcheck-unicode-security Wcomment Wdeprecated Weffc++, Qeffc++ Werror, WX Werror-all Wextra-tokens Wformat Wformat-security Wmain Wmissing-declarations Wmissing-prototypes Wpointer-arith Wreorder Wreturn-type Wshadow Wsign-compare Wstrict-aliasing Wstrict-prototypes Wtrigraphs Wuninitialized Wunknown-pragmas Wunused-function Wunused-variable Wwrite-strings
Compatibility Options x
gcc-toolchain vmv
Linking or Linker Options x
Bdynamic Bstatic Bsymbolic Bsymbolic-functions dynamic-linker F (Windows*) fixed Fm fuse-ld l L LD link MD MT no-libgcc nodefaultlibs no-intel-lib, Qno-intel-lib nostartfiles nostdlib pie pthread shared shared-intel shared-libgcc static static-intel static-libgcc static-libstdc++ T u (Linux*) v Wa Wl Wp Xlinker Zl
Miscellaneous Options x
dryrun dumpmachine dumpversion help nologo save-temps, Qsave-temps showIncludes sox, Qsox sysroot Tc TC Tp version watch
Floating-Point Operations x
Programming Tradeoffs in Floating-Point Applications Use the -fp-model, /fp Option Denormal Numbers Set the FTZ and DAZ Flags Tuning Performance Floating-Point Array Operations in a Loop Body Reduce the Impact of Denormal Exceptions Avoid Mixed Data Type Arithmetic Expressions Use Efficient Data Types IEEE Floating-Point Operations
Attributes x
align align_value allow_cpu_features concurrency_safe const cpu_dispatch, cpu_specific mpx target
Libraries x
Create Libraries Use Intel Shared Libraries on Linux Manage Libraries Redistribute Libraries When Deploying Applications Resolve References to Shared Libraries Intel's Memory Allocator Library SIMD Data Layout Templates Intel® C++ Class Libraries Intel's C++ Asynchronous I/O Extensions for Windows IEEE 754-2008 Binary Floating-Point Conformance Library Intel's Numeric String Conversion Library
SIMD Data Layout Templates x
Function Calls and Containers User-Level Interface Examples
Function Calls and Containers x
Construct an n_container Bounds
User-Level Interface x
SDLT Primitives soa1d_container aos1d_container n_container Bounds Accessors Proxy Objects Number Representation Indexes Convenience and Correctness
aos1d_container x
access_by
n_container x
Layouts Shape make_ n_container template function extent_d template function
Shape x
n_extent_generator
Bounds x
bounds_t sdlt::bounds Template Function n_bounds_t n_bounds_generator bounds_d Template Function
Accessors x
soa1d_container::accessor and aos1d_container::accessor soa1d_container::const_accessor and aos1d_container::const_accessor Accessor Concept
Proxy Objects x
Proxy ConstProxy
Number Representation x
aligned_offset fixed_offset
Indexes x
linear_index n_index_t n_index_generator index_d template function
Convenience and Correctness x
max_val min_val
Examples x
Efficiency with Structure of Arrays Example Complex SDLT Primitive Construction Example Forward Dependency Example Use of Offsets and Methods on a SDLT Primitive Example RGB to YUV Conversion Example
Intel® C++ Class Libraries x
C++ Classes and SIMD Operations Capabilities of C++ SIMD Classes Integer Vector Classes Floating-Point Vector Classes Classes Quick Reference Programming Example Intel's valarray Implementation
Integer Vector Classes x
Terms and Syntax Rules for Operators Assignment Operator Logical Operators Addition and Subtraction Operators Multiplication Operators Shift Operators Comparison Operators Conditional Select Operators Debug Operations Unpack Operators Pack Operators Clear MMX™ State Operator Integer Functions for Intel® Streaming SIMD Extensions Conversions between Fvec and Ivec
Floating-Point Vector Classes x
Fvec Syntax and Notation Data Alignment Conversions Constructors and Initialization Arithmetic Operators Minimum and Maximum Operators Logical Operators Compare Operators Conditional Select Operators for Fvec Classes Cacheability Support Operators Debug Operations Load and Store Operators Unpack Operators Move Mask Operators
Intel's C++ Asynchronous I/O Extensions for Windows x
Intel's C++ Asynchronous I/O Library for Windows Intel's C++ Asynchronous I/O Class for Windows
Intel's C++ Asynchronous I/O Library for Windows x
<span class='option'>aio_read</span> <span class='option'>aio_write</span> Example for aio_read and aio_write Functions <span class='option'>aio_suspend</span> Example for aio_suspend Function <span class='option'>aio_error</span> <span class='option'>aio_return</span> Example for aio_error and aio_return Functions <span class='option'>aio_fsync</span> <span class='option'>aio_cancel</span> Example for aio_cancel Function <span class='option'>lio_listio</span> Example for lio_listio Function Asynchronous I/O Function Errors
Intel's C++ Asynchronous I/O Class for Windows x
Template Class async_class <span class='option'>get_last_operation_id</span> wait get_status get_last_error <span class='option'>get_error_operation_id</span> stop_queue resume_queue clear_queue Example for Using async_class Template Class
IEEE 754-2008 Binary Floating-Point Conformance Library x
Intel® IEEE 754-2008 Binary Floating-Point Conformance Library and Usage Function List Homogeneous General-Computational Operations Functions <i></i>General-Computational Operations Functions Quiet-Computational Operations Functions Signaling-Computational Operations Functions Non-Computational Operations Functions
Intel's Numeric String Conversion Library x
Use Intel's Numeric String Conversion Library Function List
Macros x
ISO Standard Predefined Macros Additional Predefined Macros Use Predefined Macros to Specify Intel® Compilers
Pragmas x
Intel-Specific Pragma Reference Intel-Supported Pragma Reference
Intel-Specific Pragma Reference x
block_loop/noblock_loop distribute_point inline, noinline, forceinline ivdep loop_count nofusion novector omp target variant dispatch ompx prefetch data prefetch/noprefetch unroll/nounroll unroll_and_jam/nounroll_and_jam vector
Compilation x
Compilation Overview Supported Environment Variables Pass Options to the Linker Specify Alternate Tools and Paths Use Configuration Files Use Response Files Global Symbols and Visibility Attributes for Linux* Save Compiler Information in Your Executable Link Debug Information Ahead of Time Compilation Device Offload Compilation Considerations Use a Third-Party Compiler as a Host Compiler for SYCL Code
Optimization and Programming x
Extensions OpenMP* Support Intel® oneAPI Level Zero Vectorization High-Level Optimization Interprocedural Optimization Methods to Optimize Code Size Intel® oneAPI DPC++/C++ Compiler Math Library
OpenMP* Support x
Add OpenMP* Support Parallel Processing Model Worksharing Using OpenMP* Control Thread Allocation OpenMP* Pragmas OpenMP* Library Support OpenMP* Advanced Issues OpenMP* Implementation-Defined Behaviors OpenMP* Examples
OpenMP* Library Support x
OpenMP* Runtime Library Routines Intel® Compiler Extension Routines to OpenMP* OpenMP* Support Libraries Use the OpenMP Libraries Thread Affinity Interface OpenMP* Memory Spaces and Allocators
Intel® oneAPI Level Zero x
Intel® oneAPI Level Zero Switch Intel® oneAPI Level Zero Backend Specification Programming with the Intel® oneAPI Level Zero Backend
Vectorization x
Automatic Vectorization Explicit Vector Programming
Automatic Vectorization x
Vectorization Programming Guidelines Use Automatic Vectorization Vectorization and Loops Loop Constructs
Explicit Vector Programming x
User-Mandated or SIMD Vectorization SIMD-Enabled Functions SIMD-Enabled Function Pointers Vectorize a Loop Using the _Simd Keyword Function Annotations and the SIMD Directive for Vectorization Explicit SIMD SYCL Extension
Interprocedural Optimization x
Use Interprocedural Optimization Performance and Large Program Considerations Create a Library from IPO Objects Inline Expansion of Functions
Intel® oneAPI DPC++/C++ Compiler Math Library x
Use the Intel® oneAPI DPC++/C++ Compiler Math Library Math Function List Trigonometric Functions Hyperbolic Functions Exponential Functions Special Functions Nearest Integer Functions Remainder Functions Miscellaneous Functions Complex Functions C99 Macros
Compatibility and Portability x
Standards Conformance GCC Compatibility and Interoperability Microsoft Compatibility Port from Microsoft Visual C++* to the Intel® oneAPI DPC++/C++ Compiler Port from GCC* to the Intel® oneAPI DPC++/C++ Compiler
Port from Microsoft Visual C++* to the Intel® oneAPI DPC++/C++ Compiler x
Modify Your makefile Other Considerations
Port from GCC* to the Intel® oneAPI DPC++/C++ Compiler x
Modify Your makefiledpc Other Considerations
Intel® oneAPI DPC++/C++ Compiler Developer Guide and Reference

Tuning Performance

This section describes several programming guidelines that can help you improve the performance of floating-point applications, including:

Floating-Point Array Operations in a Loop Body

Following the guidelines below will help auto-vectorization of the loop.

  • Statements within the loop body may contain float or double operations (typically on arrays). The following arithmetic operations are supported: addition, subtraction, multiplication, division, negation, square root, MAX, MIN, and mathematical functions such as SIN and COS.
  • Writing to a single-precision scalar/array and a double scalar/array within the same loop decreases the chance of auto-vectorization due to the differences in the vector length (that is, the number of elements in the vector register) between float and double types. If auto-vectorization fails, try to avoid using mixed data types.
NOTE:

The special __m64, __m128, and __m256 datatypes are not vectorizable. The loop body cannot contain any function calls. Use of the Intel® Streaming SIMD Extensions (Intel® SSE) and Intel® Advanced Vector Extensions (Intel® AVX) intrinsics (for example, mm_add_ps) is not allowed.

Reduce the Impact of Denormal Exceptions

Denormalized floating-point values are those that are too small to be represented in the normal manner; that is, the mantissa cannot be left-justified. Denormal values require hardware or operating system interventions to handle the computation, so floating-point computations that result in denormal values may have an adverse impact on performance.

There are several ways to handle denormals to increase the performance of your application:

  • Scale the values into the normalized range

  • Use a higher precision data type with a larger range

  • Flush denormals to zero

For example, you can translate them to normalized numbers by multiplying them using a large scalar number, doing the remaining computations in the normal space, then scaling back down to the denormal range. Consider using this method when the small denormal values benefit the program design.

Consider using a higher precision data type with a larger range; for example, by converting variables declared as float to be declared as double. Understand that making the change can potentially slow down your program. Storage requirements will increase, which will increase the amount of time for loading and storing data from memory. Higher precision data types can also decrease the potential throughput of Intel® Streaming SIMD Extensions (Intel® SSE) and Intel® Advanced Vector Extensions (Intel® AVX) operations.

If you change the type declaration of a variable, you might also need to change associated library calls, unless these are generic; ; for example, cos() instead of cosf().. You should verify that the gain in performance from eliminating denormals is greater than the overhead of using a data type with higher precision and greater dynamic range.

In many cases, denormal numbers can be treated safely as zero without adverse effects on program results. Depending on the target architecture, use flush-to-zero (FTZ) options.

Avoid Mixed Data Type Arithmetic Expressions

Avoid mixing integer and floating-point (float, double, or long double) data in the same computation. Expressing all numbers in a floating-point arithmetic expression (assignment statement) as floating-point values eliminates the need to convert data between fixed and floating-point formats. Expressing all numbers in an integer arithmetic expression as integer values also achieves this. This improves runtime performance.

For example, assuming that I and J are both int variables, expressing a constant number (2.0) as an integer value (2) eliminates the need to convert the data. The following examples demonstrate inefficient and efficient code.

Inefficient code: 

int I, J;
  I = J / 2.0
;

Efficient code: 

int I, J;
  I = J / 2;

Use Efficient Data Types

In cases where more than one data type can be used for a variable, consider selecting the data types based on the following hierarchy, listed from most to least efficient:

  • char

  • short

  • int

  • long

  • long long

  • float

  • double

  • long double

NOTE:

In an arithmetic expression, you should avoid mixing integer and floating-point data.

You can use integer data types (int, int long, etc.) in loops to improve floating point performance. Convert the data type to integer data types, process the data, then convert the data to the old type.

Parent topic: Floating-Point Operations

See Also

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