MacResearch.org David W. Gohara, Ph.D.

In this episode we'll go over an example of real-world code that has been parallelized by porting to the GPU. The use of shared memory to improve performance is covered as well as a discussion of synchronization points for coordinated work within a work-group. Source code is provided.

In this episode we'll go over an example of real-world code that has been parallelized by porting to the GPU. The use of shared memory to improve performance is covered as well as a discussion of synchronization points for coordinated work within a work-group. Source code is provided.

This episode covers questions hthat were generated from the previous podcast. We'll discuss GPU layout/terminology and bank conflicts resulting from shared memory access.

This episode covers questions hthat were generated from the previous podcast. We'll discuss GPU layout/terminology and bank conflicts resulting from shared memory access.

In this episode we cover some questions regarding function calls from kernels and the use of clFinish. Also, we'll discuss basic GPU architecture, memory layout, shared memory. Thread blocks, warps and efficient data loading will also be discussed.

In this episode we cover some questions regarding function calls from kernels and the use of clFinish. Also, we'll discuss basic GPU architecture, memory layout, shared memory. Thread blocks, warps and efficient data loading will also be discussed.