With CUDA_FORCE_PTX_JIT=1, GPU binary code embedded in an application binary is ignored. Set the environment variable CUDA_FORCE_PTX_JIT=1. This can be tested by forcing the PTX to JIT-compile at application load time with following the steps:ĭownload and install the latest driver from. Applications Built Using CUDA Toolkit 10.2 or Earlier ĬUDA applications built using CUDA Toolkit versions 2.1 through 10.2 are compatible with NVIDIA Ada architecture based GPUs as long as they are built to include PTX versions of their kernels. The following sections explain how to accomplish this for an already built CUDA application. The first step towards making a CUDA application compatible with the NVIDIA Ada GPU architecture is to check if the application binary already contains compatible GPU code (at least the PTX). Verifying Ada Compatibility for Existing Applications As a consequence, any binary that runs on Ampere will be able to run on Ada (forward compatibility), but an Ada binary will not be able to run on Ampere. The NVIDIA Ada architecture is based on Ampere’s Instruction Set Architecture ISA 8.0, extending it with new instructions. To know more about building compatible applications, read Building Applications with the NVIDIA Ada GPU Architecture Support. However, application binaries that do not include PTX (only include cubins) need to be rebuilt to run on the NVIDIA Ada architecture based GPUs. In such cases, rebuilding the application is not required. If neither compatible cubin nor PTX is available, kernel launch results in a failure.Īpplication binaries that include PTX version of kernels should work as-is on the NVIDIA Ada architecture based GPUs. Otherwise, the CUDA Runtime first generates compatible cubin by JIT-compiling 1 the PTX and then the cubin is used for the execution. If a cubin compatible with that GPU is present in the binary, the cubin is used as-is for execution. When a CUDA application launches a kernel on a GPU, the CUDA Runtime determines the compute capability of the GPU in the system and uses this information to find the best matching cubin or PTX version of the kernel. To read more about cubin and PTX compatibilities see Compilation with NVCC from the CUDA C++ Programming Guide. Therefore, although it is optional, it is recommended that all applications should include PTX of the kernels to ensure forward-compatibility. For example, PTX code generated for compute capability 8.x is supported to run on compute capability 8.x or any higher revision (major or minor), including compute capability 9.x. Meaning PTX is supported to run on any GPU with compute capability higher than the compute capability assumed for generation of that PTX. At the application load time, PTX is compiled to cubin and the cubin is used for kernel execution. Kernels can also be compiled to a PTX form. For example, a cubin generated for compute capability 8.6 is supported to run on a GPU with compute capability 8.9 however, a cubin generated for compute capability 8.9 is not supported to run on a GPU with compute capability 8.6, and a cubin generated with compute capability 8.x is not supported to run on a GPU with compute capability 9.0. A cubin generated for a certain compute capability is supported to run on any GPU with the same major revision and same or higher minor revision of compute capability. Both cubin and PTX are generated for a certain target compute capability. Application Compatibility on the NVIDIA Ada GPU Architecture Ī CUDA application binary (with one or more GPU kernels) can contain the compiled GPU code in two forms, binary cubin objects and forward-compatible PTX assembly for each kernel. This document provides guidance to developers who are familiar with programming in CUDA C++ and want to make sure that their software applications are compatible with the NVIDIA Ada GPU architecture. This application note, NVIDIA Ada GPU Architecture Compatibility Guide for CUDA Applications, is intended to help developers ensure that their NVIDIA ® CUDA ® applications will run on the NVIDIA ® Ada Architecture based GPUs. NVIDIA Ada GPU Architecture Compatibility 1.1. The guide to building CUDA applications for NVIDIA Ada GPUs. NVIDIA Ada GPU Architecture Compatibility Guide for CUDA Applications
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