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Use advanced sampling and profiling methods to quickly analyze code, isolate issues, and deliver performance insight on modern CPUs, GPUs, and FPGAs.

Design code for efficient vectorization, threading, and offloading to accelerators.

Use 15 tools and libraries to build and deploy high-performance, data-centric applications. The toolkit includes the Data Parallel C++ language.

Accelerate AI pipelines by training deep neural networks, integrating trained models for inference, and running functions for data science and analyti

Create and debug C and C++ applications that are enabled for this SDK.

Transform data into rich visuals with this toolkit that includes five rendering libraries, ray tracing, denoising, rasterizing, and 3D processing.

Accelerate system bring-up and optimization to get from presilicon to production faster.

Create IoT solutions for CPUs, GPUs, FPGAs, and other accelerator architectures with this set of tools. The Intel® oneAPI Base Toolkit is required.

Create your own or customize an existing machine learning framework with this foundational set of tools.

Develop fast, Python code with essential computational packages including NumPy, SciPy, scikit-learn*, and more.

These open-source libraries and drivers accelerate packet processing and forwarding without custom switches and routers.

This technology enables remote, secure platform management when connected to AC power with network connections.