For more on this topic see Using pipelining in multicore LabView and Using data parallelism in multicore LabView. Until recently, advances in computing hardware have provided significant increases in ...

Task parallelism is perhaps the most general approach to parallel processing. In task parallel programs, different operations (i.e., tasks) are performed simultaneously; sometimes the tasks operate on ...

Abstract: Current deep learning compilers have made significant strides in optimizing computation graphs for single- and multi-model scenarios. However, they lack specific optimizations for ...

Abstract: Task parallelism schemes with a multi-core system are widely used through various applications nowadays to obtain better throughput. Most of previous works will try to find maximum degree of ...

Codelets and tasks When StarPU is initialized, it creates a set of worker threads. Usually each CPU core gets its own worker thread. Depending on the configuration, one or more CPU cores (and GPU ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

Microsoft has provided support for parallel programming in .Net Framework to leverage the benefits of multi core systems. In this post, I will present a discussion on the support for Parallel ...

Data parallelism is achieved in the processEmployeesAndMetricsByDepartment function, where tasks involving querying and processing employees based on their department ...

“The first law of massive parallelism is the foundation for massive marketing that supports massive budgets that supports the search for massive parallelism,” Gordon Bell, 1992 [2]. For many years ...