![]() The on-chip shared memory allows parallel tasks running on theseĬores to share data without sending it over the system memory bus. Resources including a register file and a shared memory. This configuration also allows simultaneousĬomputation on the CPU and GPU without contention for memory resources.ĬUDA-capable GPUs have hundreds of cores that can collectively run thousands of computing threads. The CPU and GPU are treated as separate devices that have their own memory spaces. As such, CUDA can be incrementally applied to existing applications. The CPU, and parallel portions are offloaded to the GPU. Serial portions of applications are run on Support heterogeneous computation where applications use both the CPU and GPU. ![]() With CUDA C/C++, programmers can focus on the task of parallelization of the algorithms rather than Provide a small set of extensions to standard programming languages, like C, that enable a straightforward implementation.CUDA was developed with several design goals in mind: ![]()
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