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Nvidia's CUDA is closed-source, whereas AMD ROCm is open source. There is open-source software built on top of the closed-source CUDA, for instance RAPIDS. CUDA is able to run on consumer GPUs, whereas ROCm support is mostly offered for professional hardware such as AMD Instinct and AMD Radeon Pro.
GPUOpen HIP: A thin abstraction layer on top of CUDA and ROCm intended for AMD and Nvidia GPUs. Has a conversion tool for importing CUDA C++ source. Supports CUDA 4.0 plus C++11 and float16. ZLUDA is a drop-in replacement for CUDA on AMD GPUs and formerly Intel GPUs with near-native performance. [33]
Nvidia launched CUDA in 2006, a software development kit (SDK) and application programming interface (API) that allows using the programming language C to code algorithms for execution on GeForce 8 series and later GPUs. ROCm, launched in 2016, is AMD's open-source response to CUDA. It is, as of 2022, on par with CUDA with regards to features ...
ROCm HIP targets Nvidia GPU, AMD GPU, and x86 CPU. HIP is a lower-level API that closely resembles CUDA's APIs. [47] For example, AMD released a tool called HIPIFY that can automatically translate CUDA code to HIP. [48] Therefore, many of the points mentioned in the comparison between CUDA and SYCL also apply to the comparison between HIP and ...
AMD support Year introduced Introduced with Rendering Computing / ROCm; Vulkan [17] OpenGL [18] Direct3D HSA OpenCL; Wonder: Fixed-pipeline [a] 1000 nm 800 nm — — — — — Ended 1986 Graphics Solutions Mach: 800 nm 600 nm 1991 Mach8 3D Rage: 500 nm 5.0 1996 3D Rage Rage Pro: 350 nm 1.1 6.0 1997 Rage Pro Rage 128: 250 nm 1.2 1998 Rage 128 ...
Codeplay has released an open-source layer [23] [24] [25] to allow oneAPI and SYCL/DPC++ to run atop Nvidia GPUs via CUDA. University of Heidelberg has developed a SYCL/DPC++ implementation for both AMD and Nvidia GPUs. [26] Huawei released a DPC++ compiler for their Ascend AI Chipset [27]
AMD's data center revenue rose 122% year over year to a record $3.5 billion in its fiscal Q3, ended Sept. 28. ... Nvidia: if you invested $1,000 when we doubled down in 2009, you’d have $338,855!*
CuPy supports Nvidia CUDA GPU platform, and AMD ROCm GPU platform starting in v9.0. [ 4 ] [ 5 ] CuPy has been initially developed as a backend of Chainer deep learning framework, and later established as an independent project in 2017.