2.1. Supported Platforms

A platform refers to the combination of your target machine’s OS version, CPU, and toolchain (compiler or Visual Studio). Each platform has an RTI architecture name, which is a shorthand way to identify the platform. The “target” is the machine where you will deploy your completed application. (As opposed to a “host”, which is where you will be developing the application.)

For example, if you have a 64-bit Windows machine with Visual Studio® 2017, the architecture name is x64Win64VS2017. For a 64-bit Linux machine with gcc version 7.3.0, the architecture name is x64Linux4gcc7.3.0.

The following table lists the supported operating systems and their architecture names.

Once you know your architecture name, use the tables in the Core Libraries Platform Notes to see which products/features are supported. You will also need to know your architecture name when downloading/installing various Connext libraries.

Notice that the lower part of the table shows architectures that are Custom Target Libraries, only available on demand by contacting sales@rti.com.

Table 2.1 Supported Platforms for Connext Professional

Operating System

Version

CPU Architecture

Toolchain

RTI Architecture [7]

Android™ [22]

Android 12, 14

ARM64

clang 12.0.8 (ndk r23b)

arm64Android12clang12.0.8ndkr23b [22]

AOSP 14

ARM64

clang 17.0.2

arm64AndroidAOSP14clang17.0.2

Linux® (ARM®)

Ubuntu® 18.04 LTS

ARMv7

gcc 7.5.0

armv7Linux4gcc7.5.0 [6]

Ubuntu 18.04 LTS, 22.04 LTS, 24.04 LTS

ARMv8

gcc 7.3.0

armv8Linux4gcc7.3.0

Linux (Intel®)

Red Hat® Enterprise Linux 8, 9, Ubuntu 18.04 LTS, 20.04 LTS, 22.04 LTS, 24.04 LTS

x64

gcc 7.3.0

x64Linux4gcc7.3.0 [10]

Ubuntu 22.04 LTS

x64

clang 15.0.1

x64Linux5Unreal5.2clang15 [30]

macOS®

macOS 11, 12, 13, 14 (Darwin 20, 21, 22)

x64

clang 12.0, clang 13.0, clang 14.0, clang 15.0

x64Darwin20clang12.0

macOS 11, 12, 13, 14, 15 (Darwin 20, 21, 22)

ARM64

clang 12.0, clang 13.0, clang 14.0, clang 15.0, clang 16.0

arm64Darwin20clang12.0

QNX®

QNX Neutrino 7.1

ARMv8

qcc_cxx 8.3.0 (LLVM C++ library)

armv8QNX7.1qcc_cxx8.3.0

x64

qcc_cxx 8.3.0 (LLVM C++ library)

x64QNX7.1qcc_cxx8.3.0

QNX Neutrino 8.0 [40], 8.0.2

ARMv8

qcc_cxx 12.2.0 (LLVM C++ library)

armv8QNX8.0qcc_cxx12.2.0

x64

qcc_cxx 12.2.0 (LLVM C++ library)

x64QNX8.0qcc_cxx12.2.0

VxWorks®

VxWorks 23.09

x64

llvm 16.0

x64Vx23.09llvm16.0

x64

llvm 16.0

x64Vx23.09llvm16.0_rtp

Windows®

Windows 10 [9], 11, Windows Server 2016, 2022

x64

VS2017 VS2019 VS2022

x64Win64VS2017

Custom Target Libraries available on demand

Linux (Intel)

RedHawk™ Linux 8.4.1

x64

gcc 8.5.0

x64RedHawk8.4gcc8.5.0

x86

gcc 8.5.0

i86RedHawk8.4gcc8.5.0

Red Hat Enterprise Linux 7, 7.3, 7.5, 7.6, CentOS 7.0

x64

gcc 4.8.2

x64Linux3gcc4.8.2

x86

gcc 4.8.2

i86Linux3gcc4.8.2

Red Hat Enterprise Linux 8, 9, Ubuntu 18.04 LTS, 20.04 LTS, 22.04 LTS

x64

gcc 7.3.0

x64Linux4gcc7.3.0_CXX11_ABI_0

SUSE® Linux Enterprise Server 15 SP2, SP7

x64

gcc 7.5.0

x64Linuxgcc7.5.0

Ubuntu 16.04 LTS

x86

gcc 5.4.0

i86Linux3gcc5.4.0

FACE Linux (Intel)

Red Hat Enterprise Linux 8, 9, Ubuntu 18.04 LTS, 20.04 LTS, 22.04 LTS

x64

gcc 7.3.0

x64Linux4gcc7.3.0FACE_GP [12]

LynxOS®

LynxOS 7.3.1

ppce6500

gcc 7.1.0

ppce6500Lynx7.3gcc7.1

QNX

QNX 7.0.4

ARMv8

qcc_cxx 5.4.0 (LLVM C++ library)

armv8QNX7.0.0qcc_cxx5.4.0

x64

qcc_cxx 5.4.0 (LLVM C++ library)

x64QNX7.0.0qcc_cxx5.4.0

x64

qcc_gpp 5.4.0 (GNU C++ library)

x64QNX7.0.0qcc_gpp5.4.0

QNX 7.0.4 [24]

ARMv7

qcc_cxx 5.4.0 (LLVM C++ library)

armv7QNX7.0.0qcc_cxx5.4.0 [6]

QNX 7.1

ARMv8

qcc_gpp 8.3.0 (GNU C++ library)

armv8QNX7.1qcc_gpp8.3.0

QOS 2.2 (QNX OS for Safety)

ARMv8

qcc_cxx 8.3.0 (LLVM C++ library)

armv8QOS2.2qcc_cxx8.3.0

VxWorks

VxWorks 23.03

PPC (e6500, 32-bit)

llvm 17.0.6.1

ppce6500Vx23.03llvm15.0_rtp

VxWorks 24.03

PPC (e500v2)

llvm 17.0.6.1

ppce500v2Vx24.03llvm17.0

llvm 17.0.6.1

ppce500v2Vx24.03llvm17.0_rtp

VxWorks 7.0 (SR0630)

x64

llvm 8.0.0.2

x64Vx7SR0630llvm8.0.0.2

x64

llvm 8.0.0.2

x64Vx7SR0630llvm8.0.0.2_rtp

Windows

Windows 10 [9], Windows Server 2016

x86

VS 2017 VS2019

i86Win32VS2017

Windows 10, Windows Server 2012 R2, 2016

x64

VS 2015

x64Win64VS2015

Windows 10, Windows Server 2016

x86

VS 2015

i86Win32VS2015

2.1.1. Footnotes

These footnotes are used in the above table.

Table 2.2 Footnotes for Supported Platforms Table

6

These libraries require a hardware FPU in the processor and are compatible with systems with hard-float libc. See the Platform Notes for compiler flag details.

9

Per Microsoft, this should be compatible with Windows 10 IoT Enterprise with Windows native app.

10

This should also work on WindRiver Linux 9

12

Does not support request-reply API or Ping/Spy

22

Advanced example generation in code generator not supported

24

Tested with QNX 7.0.0 kernel

30

Target libraries for Unreal 5.2

40

Earliest versions of com.qnx.qnx800.target.microkernel.core (QNX® SDP 8.0 Kernel and libc) component are not supported

Update this component in your QNX 8.0 SDP installation to 2.0.2.00388T202406131303L or higher (Stable (GA8.0.1) July 09 2024) before generating QNX system image