[3] SYCL is a royalty-free, cross-platform abstraction layer that builds on the underlying concepts, portability and efficiency inspired by OpenCL that enables code for heterogeneous processors to be written in a “single-source” style using completely standard C++.

[38] In the Khronos Group realm, OpenCL and Vulkan are the low-level non-single source APIs, providing fine-grained control over hardware resources and operations.

OpenCL is widely used for parallel programming across various hardware types, while Vulkan primarily focuses on high-performance graphics and computing tasks.

It enables developers to write code for heterogeneous computing systems, including CPUs, GPUs, and other accelerators, using a single-source approach.

In fact, Intel released a tool called SYCLOMATIC that automatically translated code from CUDA to SYCL.

[38] SYCL extends the C++ AMP features, relieving the programmer from explicitly transferring data between the host and devices by using buffers and accessors.

[47] For example, AMD released a tool called HIPIFY that can automatically translate CUDA code to HIP.

[49] ROCm HIP has some similarities to SYCL in the sense that it can target various vendors (AMD and Nvidia) and accelerator types (GPU and CPU).

However, unlike SYCL, Raja introduces an abstraction layer over other programming models like CUDA, HIP, OpenMP, and others.

[39] Similar to Kokkos, Raja is more tailored for HPC use cases, focusing on performance and scalability in high-performance computing environments.

In contrast, SYCL supports a broader range of devices, making it more versatile for different types of applications beyond just HPC.

This development will enhance Raja's portability and flexibility, allowing it to leverage SYCL's capabilities and expand its applicability across a wider array of hardware platforms.

[39] OpenMP targets computational offloading to external accelerators,[58] primarily focusing on multi-core architectures and GPUs.

SYCL, on the other hand, is oriented towards a broader range of devices due to its integration with OpenCL, which enables support for various types of hardware accelerators.

[59] OpenMP uses a pragma-based approach, where the programmer annotates the code with directives, and the compiler handles the complexity of parallel execution and memory management.

This high-level abstraction makes it easier for developers to parallelize their applications without dealing with the intricate details of memory transfers and synchronization.

[64] By leveraging SYCL's capabilities, developers can write standard C++ code that seamlessly executes on heterogeneous computing environments.