This post is Topic #3 (post 2) in our series Parallel Code: Maximizing your Performance Potential. In my previous post, I provided an introduction to the various types of memory available for use in a CUDA application.…
This post is Topic #3 (part 1) in our series Parallel Code: Maximizing your Performance Potential. CUDA devices have several different memory spaces: Global, local, texture, constant, shared and register memory. Each type of memory on the…
This post is Topic #2 (part 2) in our series Parallel Code: Maximizing your Performance Potential. In my previous post, CUDA Host/Device Transfers and Data Movement, I provided an introduction into the bottlenecks associated with host/device transfers…
This post is Topic #2 (part 1) in our series Parallel Code: Maximizing your Performance Potential. In post #1, I discussed a few ways to optimize the performance of your application via controlling your threads and provided…
This post is Topic #1 in our series Parallel Code: Maximizing your Performance Potential. Regardless of the environment or architecture you are using, one thing is certain: you must properly manage the threads running in your application to…
No matter what the purpose of your application is, one thing is certain. You want to get the most bang for your buck. You see research papers being published and presented making claims of tremendous speed increases…
This week NVIDIA provided a tutorial outlining first steps for GPU acceleration using OpenACC and CUDA. This was offered as part of the “GPUs Accelerating Research” week at Northeastern University and Boston University. After attending, it seemed…
I think everyone in the HPC arena has heard plenty about GPUs. GPUs aren’t sophisticated like CPUs, but they provide raw performance for those who know how to use them. The question for those who have large…
