Summary: NVIDIA has released CUDA Toolkit 12.0, a significant update to its parallel computing platform. This release focuses on new programming models and CUDA application acceleration through new hardware capabilities, particularly for the NVIDIA Hopper and NVIDIA Ada Lovelace architectures. Key features include enhanced memory bandwidth, higher clock rates, increased streaming multiprocessor (SM) count, and significant performance improvements through updated CUDA dynamic parallelism APIs.
Unlocking New Capabilities with CUDA Toolkit 12.0
NVIDIA’s CUDA Toolkit 12.0 marks a major milestone in the evolution of its parallel computing platform. This release is designed to harness the full potential of the NVIDIA Hopper and NVIDIA Ada Lovelace architectures, offering developers a range of new features and improvements.
Key Features and Enhancements
- Support for New Architectures: CUDA 12.0 introduces support for the NVIDIA Hopper and NVIDIA Ada Lovelace architectures, providing developers with the tools to leverage these new GPUs.
- Enhanced Memory Bandwidth: The toolkit offers enhanced memory bandwidth, higher clock rates, and increased streaming multiprocessor (SM) count, all of which are instantly beneficial to CUDA applications.
- Improved CUDA Dynamic Parallelism: The updated CUDA dynamic parallelism APIs bring substantial performance improvements, including reduced launch overhead and the ability to launch graphs from the device.
- Programmable Capabilities: The toolkit exposes programmable functionality for many features of the Hopper and Ada Lovelace architectures, including TMA operations, asynchronous transaction barriers, and cooperative grid array (CGA) relaxed barriers.
- CUDA Graphics API Enhancements: The CUDA graphics API has been improved, offering better performance and new features.
- Support for New Compilers: CUDA 12.0 supports the GCC 12 host compiler and C++ 20, including modules for importing and exporting entities between translation units.
- JIT LTO Support: The toolkit introduces a new library, nvJitLink, for JIT LTO, enhancing performance and flexibility.
Detailed Look at New Features
Programmable Functionality
- TMA Operations: The toolkit provides public PTX for TMA operations, including bulk operations and 32x Ultra xMMA (including FP8/FP16).
- Asynchronous Transaction Barriers: Support for Hopper asynchronous transaction barriers in C++ and PTX.
- Cooperative Grid Array (CGA) Relaxed Barriers: Introduced C intrinsics for CGA relaxed barrier support.
- Programmatic L2 Cache to SM Multicast: Available for Hopper GPUs to provide faster combined-math arithmetic operations.
CUDA Graphs API Enhancements
- Scheduling Graph Launches: The ability to schedule graph launches from GPU device-side kernels by calling built-in functions.
- Refactored cudaGraphInstantiate() API: Removed unused parameters to streamline the API.
- Virtual Memory Management: Added support for using virtual memory management (VMM) APIs with GPUs masked by CUDA_VISIBLE_DEVICES.
CUDA Dynamic Parallelism
- Substantial Performance Improvements: The updated CUDA dynamic parallelism APIs offer significant performance gains compared to the legacy APIs.
- Reduced Launch Overhead: Improved launch efficiency for dynamic parallelism.
Impact on Developers
The CUDA Toolkit 12.0 is a powerful tool for developers working with NVIDIA GPUs. It provides the necessary features and improvements to create, improve, and deploy applications on GPU-accelerated embedded systems, desktop workstations, business data centers, cloud-based platforms, and HPC supercomputers.
#Table: Key Features of CUDA Toolkit 12.0
| Feature | Description |
|---|---|
| Support for New Architectures | Support for NVIDIA Hopper and NVIDIA Ada Lovelace architectures. |
| Enhanced Memory Bandwidth | Improved memory bandwidth, higher clock rates, and increased SM count. |
| Improved CUDA Dynamic Parallelism | Substantial performance improvements and reduced launch overhead. |
| Programmable Capabilities | Exposed programmable functionality for TMA operations, asynchronous transaction barriers, and CGA relaxed barriers. |
| CUDA Graphics API Enhancements | Improved performance and new features in the CUDA graphics API. |
| Support for New Compilers | Support for GCC 12 host compiler and C++ 20. |
| JIT LTO Support | Introduction of nvJitLink library for JIT LTO. |
This release is a testament to NVIDIA’s commitment to advancing parallel computing and providing developers with the tools they need to push the boundaries of what is possible with GPU-accelerated computing.
Conclusion
CUDA Toolkit 12.0 is a significant step forward in parallel computing, offering developers the tools to unlock the full potential of the NVIDIA Hopper and NVIDIA Ada Lovelace architectures. With its enhanced memory bandwidth, improved CUDA dynamic parallelism, and programmable capabilities, this release is set to empower developers to create more efficient and powerful applications.