Intel® oneAPI DPC++ Library (oneDPL)
Speed Up DPC++ (SYCL*) Kernels on CPUs and GPUs
A Performance and Productivity Library for Accelerated Computing
The Intel® oneAPI DPC++ Library (oneDPL) is a companion to the Intel® oneAPI DPC++/C++ Compiler and provides an alternative for C++ developers who create heterogeneous applications and solutions. Its APIs are based on familiar standards—C++ STL, Parallel STL (PSTL), Boost.Compute, and SYCL*—to maximize productivity and performance across CPUs and GPUs.
- Allows explicit use of the C++ STL API within accelerated DPC++ kernels
- Streamline cross-architecture programming with Boost.Compute and PSTL algorithm extensions
- Increase the successful application of parallel algorithms with custom iterators
Download the Stand-Alone Version
A stand-alone download of oneDPL is available. You can download binaries from Intel or choose your preferred repository.
Help oneDPL Evolve
oneDPL is part of the oneAPI industry standards initiative. We welcome you to participate.
Download as Part of the Toolkit
oneDPL is included as part of the Intel® oneAPI Base Toolkit, which is a core set of tools and libraries for developing high-performance, data-centric applications across diverse architectures.
Features
Inline Accelerator Targeting
Use device and host containers to target GPUs or run your code across multi-node CPUs.
Optimized C++ Standard Algorithms
Access parallelized C++17 algorithms and utilities for efficient application development and deployment on a variety of hardware.
Integrated with Intel® DPC++ Compatibility Tool
This library complements all Intel oneAPI DPC++ components to simplify migration of CUDA* applications to SYCL code.
Benchmarks
Documentation & Code Samples
Documentation
Code Samples
Use the C++ Standard Template Library (STL) Extended API from oneDPL
See how to write heterogeneous program to offload to a CPU or GPU using upper_bound and reduce_by_segment API to implement both dense and sparse histograms.
Use the extended API in oneDPL with the counting and zip iterator extensions to implement a stable sort by key algorithm that can be offloaded to a CPU or GPU.
Use the C++ STL and Parallel STL API for CPU & GPU Offload
This sample implements the Maxloc reduction search with direct SYCL code, and then simplifies it using oneDPL with three ways of passing data: in a standard container, in the SYCL buffer, or by using unified shared memory.
Learn how the oneDPL parallel STL policy and oneDPL algorithms help to accelerate a gamma correction's nonlinear operations to encode and decode the luminance of each pixel of an image.
View the oneAPI Samples Catalog
How to work with code samples:
Training
Understand oneDPL
- oneDPL Overview [6:19]
- oneDPL Empowers Your C++ Application for Cross-device Parallel Programming with SYCL
Extend Parallelization to GPU
Hands-On Coding: Parallel Algorithms, Search Functions, and More
- Reduction Operations in oneAPI Using SYCL or oneAPI DPC++ Library [48:02]
- More Productive and Performant C++ Programming with oneDPL
Specifications
Processors:
- Intel® Core™ processors Gen6 and newer
- Intel® Xeon® processors
GPUs:
- Intel® UHD Graphics for 11th generation Intel processors or newer
- Intel® Iris® Xe graphics
- Intel® Arc™ graphics
- Intel® Data Center GPU Flex Series
- Intel® Data Center GPU Max Series
Host and target operating systems:
- Windows
- Linux
Languages:
- SYCL
- C++
Development environments (optional):
- Microsoft Visual Studio*, Microsoft Visual Studio Code
- Eclipse* IDE
For more information, see the system requirements.
Get Help
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