Summary:

NVIDIA’s CUDA Toolkit 12.4 introduces the nvFatbin library, a significant advancement in GPU programming that simplifies the creation of fatbins at runtime. Fatbins are containers for multiple versions of code, essential for storing different architectures’ code, such as sm_61 and sm_90. This new library streamlines the dynamic generation of these binaries, making it an invaluable tool for developers working with NVIDIA GPUs.

Runtime Fatbin Creation: A Game-Changer for NVIDIA GPU Developers

Introduction

The NVIDIA CUDA Toolkit 12.4 marks a significant milestone in GPU programming with the introduction of the nvFatbin library. This new library allows for the creation of fatbins at runtime, a feature that greatly simplifies the dynamic generation of these binaries. In this article, we will explore the main ideas behind this development and how it benefits developers working with NVIDIA GPUs.

What are Fatbins?

Fatbins, or NVIDIA device code fat binaries, are containers that store multiple versions of code to ensure compatibility across different GPU architectures. For example, a fatbin can contain code for both sm_61 and sm_90 architectures, making it essential for developers who need to support various GPU models.

The Challenge of Creating Fatbins

Before the introduction of the nvFatbin library, generating a fatbin required using the command line tool fatbinary, which was not conducive to dynamic code generation. This process involved writing generated code to a file, calling fatbinary through exec, and handling the outputs, making it cumbersome and inefficient.

How nvFatbin Simplifies Fatbin Creation

The nvFatbin library streamlines the process of creating fatbins by enabling the programmatic creation of these binaries without the need for file operations or command line parsing. This development significantly reduces the complexity of dynamically generating fatbins, making it an invaluable tool for developers working with NVIDIA GPUs.

Creating a Fatbin with nvFatbin

Creating a fatbin at runtime using the nvFatbin library involves several steps:

  1. Create a handle: A handle is created to reference the relevant pieces of device code.

    nvFatbinCreate(&handle, numOptions, options);

  2. Add device code: The device code is added to the fatbin using functions specific to the type of input, such as CUBIN, PTX, or LTO-IR.

    nvFatbinAddCubin(handle, data, size, arch, name);
nvFatbinAddPTX(handle, data, size, arch, name, ptxOptions);
nvFatbinAddLTOIR(handle, data, size, arch, name, ltoirOptions);

  3. Retrieve the fatbin: The resultant fatbin is then retrieved after allocating a buffer to ensure sufficient space.

    nvFatbinSize(linker, &fatbinSize);
void* fatbin = malloc(fatbinSize);
nvFatbinGet(handle, fatbin);

  4. Clean up: The handle is cleaned up.

    nvFatbinDestroy(&handle);

Offline Fatbin Generation with NVCC

For offline fatbin generation, developers can use the NVCC compiler with the -fatbin option. This method allows for the creation of fatbins containing multiple entries for different architectures, ensuring compatibility across various GPU models.

Compatibility and Benefits

The nvFatbin library guarantees compatibility with CUDA inputs from the same major version or lower. This means that a fatbin created with nvFatbin from CUDA Toolkit 12.4 will work with code generated by any CUDA Toolkit 12.X or earlier but is not guaranteed to work with future versions like CUDA Toolkit 13.0.

The Bigger Picture

The introduction of nvFatbin completes the suite of runtime compiler components, including nvPTXCompiler, NVRTC, and nvJitLink. These tools interact seamlessly, allowing developers to compile, link, and generate fatbins dynamically, ensuring optimal performance and compatibility across different GPU architectures.

Table: Key Functions of nvFatbin Library

Function Description
nvFatbinCreate Creates a new handle for fatbin creation.
nvFatbinAddCubin Adds a CUBIN to the fatbin.
nvFatbinAddPTX Adds PTX to the fatbin.
nvFatbinAddLTOIR Adds LTO-IR to the fatbin.
nvFatbinSize Queries the size of the created fatbin.
nvFatbinGet Retrieves the completed fatbin.
nvFatbinDestroy Destroys the fatbin creator handle.

Table: Benefits of Using nvFatbin

Benefit Description
Runtime Creation Allows for dynamic generation of fatbins.
Simplified Process Reduces complexity by eliminating file operations and command line parsing.
Compatibility Ensures compatibility with CUDA inputs from the same major version or lower.
Optimized Performance Enables optimal performance across different GPU architectures.

Table: Comparison of Offline and Runtime Fatbin Generation

Method Description
Offline with NVCC Uses NVCC compiler with -fatbin option for offline generation.
Runtime with nvFatbin Uses nvFatbin library for dynamic generation at runtime.

Table: Key Components of Runtime Compiler Suite

Component Description
nvPTXCompiler Compiles PTX to machine code.
NVRTC Runtime compiler for CUDA C++.
nvJitLink Links device code at runtime.
nvFatbin Creates fatbins at runtime.

Conclusion

The nvFatbin library in CUDA Toolkit 12.4 marks a significant advancement in GPU programming, simplifying the creation of flexible and compatible fatbins at runtime. This enhancement not only streamlines the development process but also ensures that code remains optimized and compatible for future GPU architectures, making it an essential tool for developers working with NVIDIA GPUs.