关于cuobjdump输出中code version含义及sm_20程序兼容sm_30的问询

Great questions! Let's unpack each one clearly:

The code version you're seeing is an internal version identifier for the binary code stored in the fatbin. It maps to the specific version of either the SASS (native GPU assembly) or PTX (Parallel Thread Execution) ISA (Instruction Set Architecture) that the binary was compiled against.

• For the Fatbin elf code (which is SASS for sm_20), the version [1,7] corresponds to the SASS instruction set version tailored for the Fermi architecture. This number is tied to the CUDA Toolkit version used during compilation—each toolkit release updates these internal versions to align with new hardware features or optimizations.
• For the Fatbin ptx code, the version [5,0] refers to PTX ISA version 5.0. PTX versions are directly linked to CUDA Toolkit releases (PTX 5.0 launched around CUDA 7.x), and they define the set of virtual instructions the JIT compiler can translate into native SASS for a target GPU.

While this specific field isn't prominently highlighted in the cuobjdump man page, it's used by the CUDA driver to validate compatibility and ensure it can correctly parse and execute the binary code.

Your intuition is spot-on—yes, this executable should run smoothly on an sm_30 device. Here's the breakdown:

• The executable includes PTX code targeted at sm_20. The CUDA driver's Just-In-Time (JIT) compiler will automatically translate this sm_20 PTX into native SASS code optimized for the sm_30 (Kepler) architecture. Kepler is a newer architecture than Fermi (sm_20), so it supports all the features required by the sm_20 PTX, plus additional capabilities.
• Even though there's no precompiled sm_30 SASS in the fatbin, the presence of PTX ensures compatibility with any GPU architecture backward-compatible with sm_20—this includes all Kepler, Maxwell, Pascal, Volta, Turing, Ampere, and later architectures.

The only edge case where this might fail is if the executable relied on a niche sm_20-exclusive feature that was removed in later architectures, but NVIDIA maintains strong backward compatibility for PTX code, so this scenario is extremely rare.

内容的提问来源于stack exchange，提问作者Dean