CUDA 5 introduces several new tools and features that make it easier than ever to add GPU acceleration to your applications, including:
New Nsight, Eclipse Edition helps you explore the power of GPU computing with the productivity of Eclipse on Linux and MacOS
- Develop, debug, and profile your GPU application all within a familiar Eclipse-based IDE
- Integrated expert analysis system provides automated performance analysis and step-by-step guidance to fix performance bottlenecks in the code
- Easily port CPU loops to CUDA kernels with automatic code refactoring
- Semantic highlighting of CUDA code makes it easy to differentiate GPU Code from CPU code
- Integrated CUDA code samples makes it quick and easy to get started
- Generate code faster with CUDA aware auto code completion and inline help
GPU callable libraries now possible with GPU Library Object Linking
- Compile independent sources to GPU object files and link together into a larger application
- Design plug-in APIs that allow developers to extend the functionality of your kernels
- Efficient and familiar process for developing large GPU applications
- Enables 3rd party ecosystem for GPU callable libraries
GPUDirect RDMA provides fastest possible communication between GPUs and other PCI-E devices
- Direct memory access (DMA) supported between NIC and GPU without the need for CPU-side data buffering
- Significantly improved MPISendRecv efficiency between GPU and other nodes in a network
- Eliminates CPU bandwidth and latency bottlenecks
- Works with variety of 3rd party network and storage devices
Dynamic Parallelism enables programmers to easily accelerate parallel nested loops on the new Kepler GK110 GPUs
- Developers can easily spawn new parallel work from within GPU code
- Minimizes the back and forth between the CPU and GPU
- Enables GPU acceleration for a broader set of popular algorithms, including adaptive mesh refinement used in aerospace and automotive computational fluid dynamics (CFD) simulations
- Supported natively on Kepler II architecture GPUs, preview programming guide and whitepaper available today
Watch the overview of CUDA 5.0:
