CUDAlike

CUDAlike is a cross-platform, CUDA-inspired framework designed to enable GPU-accelerated computing across non-NVIDIA devices. It provides an architecture and API surface intended to resemble CUDA, including a kernel execution model, a memory hierarchy, and host-side runtime support, while targeting multiple vendor backends.

The core idea of CUDAlike is portability. It exposes a kernel programming model with thread blocks and grids, and a device function mechanism that mirrors familiar CUDA concepts. The memory model typically includes global, shared, and constant memory spaces, with APIs for memory allocation, transfers, and synchronization. A host API allows launching kernels, querying device properties, and managing streams or queues to enable overlap of computation and data movement.

Implementation and backends are designed to be modular. The framework relies on a front-end language compatible with C/C++, and a compiler stack that can emit code for various backends such as AMD or Intel GPUs, as well as accelerator APIs like Vulkan Compute or OpenCL where available. The runtime handles contexts, module loading, asynchronous execution, and error reporting, aiming to provide a consistent programming experience across platforms.

History and development have been community-driven, with initial discussions in the late 2010s and public releases beginning in the early 2020s. It has seen adoption primarily in research, education, and prototype workflows where portability across device vendors is valued over peak CUDA performance. The project is open-source and released under a permissive license, with ongoing work focused on API compatibility, ecosystem tooling, and library support.

See also: CUDA, ROCm, SYCL, OpenCL, Vulkan Compute.