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A [https://en.wikipedia.org/wiki/Parallel_programming_model parallel programming model] for GPGPU can be [https://en.wikipedia.org/wiki/Data_parallelism data-parallel], [https://en.wikipedia.org/wiki/Task_parallelism task-parallel], a mixture of both, or with libraries and offload-directives also [https://en.wikipedia.org/wiki/Implicit_parallelism implicitly-parallel]. Single GPU threads (work-items in OpenCL) contain the kernel to be computed and are coupled to a block (work-group in OpenCL), one or multiple blocks work-group form the grid (NDRange in OpenCL) to be executed on the GPU device. The members of a block resp. work-group execute the same kernel, can be usually synchronized and have access to the same scratch-pad memory, with an architecture limit of how many threads work-items a block work-group can hold and how many threads can run in total concurrently on the device. {| class="wikitable" style="margin:auto"|+ Terminology|-! OpenCL Terminology !! CUDA Terminology|-| Kernel || Kernel|-| Compute Unit || Streaming Multiprocessor|-| Processing Element || CUDA Core|-| Work-Item || Thread|-| Work-Group || Block|-| NDRange || Grid|-|} ==Thread Examples== Nvidia GeForce GTX 580 (Fermi, CC2) <ref>[https://en.wikipedia.org/wiki/CUDA#Technical_Specification CUDA Technical_Specification on Wikipedia]</ref> * Warp size: 32* Maximum number of threads per block: 1024* Maximum number of resident blocks per multiprocessor: 32* Maximum number of resident warps per multiprocessor: 64* Maximum number of resident threads per multiprocessor: 2048  AMD Radeon HD 7970 (GCN) <ref>[https://www.olcf.ornl.gov/wp-content/uploads/2019/10/ORNL_Application_Readiness_Workshop-AMD_GPU_Basics.pdf AMD GPU Hardware Basics]</ref> * Wavefront size: 64* Maximum number of work-items per work-group: 1024* Maximum number of work-groups per compute unit: 40* Maximum number of Wavefronts per compute unit: 40* Maximum number of work-items per computer unit: 2560