Apply the concepts of parallelism and distributed memory computing to your code to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
To efficiently utilize all available resources for the task concurrency application on heterogeneous platforms, designers need to understand the memory architecture, the thread utilization on each platform, the pipeline to offload the workload to different platforms. To relieve designers of the burden of implementing the necessary infrastructures, the Heterogeneous Streaming (hStreams) library...
The latest Intel® Architecture Instruction Set Extensions Programming Reference includes the definition of Intel® Advanced Vector Extensions 512 (Intel® AV