Intel director James Reinders explains the difference between task and data parallelism, and how there is a way around the limits imposed by Amdahl's Law... I'm James Reinders, and I'm going to cover ...

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 ...

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 ...

Data parallelism is an approach towards parallel processing that depends on being able to break up data between multiple compute units (which could be cores in a processor, processors in a computer, ...

One of the things to avoid when it comes to parallelism is working with raw threads. Abstraction offers a way around the issue, by avoiding the need to deal with low-level details of parallel systems, ...

Multicore processors are here to stay and the number of cores that we'll see packed onto a single chip is only going to increase. That's because Moore's Law is only indirectly about performance; it's ...

Huge volumes of data need near-supercomputer power to process and analyze it all. You can get there with the .NET Task Parallel Library. As Web and mobile applications face the challenge of quickly ...

Take advantage of lock-free, thread-safe implementations in C# to maximize the throughput of your .NET or .NET Core applications. Parallelism is the ability to have parallel execution of tasks on ...

Language Integrated Query, also known as LINQ, is a query execution pipeline that adds query capabilities to languages targeted at the managed environment of .Net. Parallel LINQ, or PLINQ, is a query ...

As hardware designers turn toward multicore processors to improve computing power, software programmers must find new programming strategies that harness the power of parallel computing. One technique ...