Feature: System design


Active Silicon FireBird frame grabbers M


GPUs for faster image and video processing


By Frans Vermeulen, Head of Sales and Marketing, Active Silicon


odern graphics processing units (GPUs) are extremely efficient at processing images and graphics. Their architecture makes them very well suited to applications where large blocks of data must be processed in parallel – like


in embedded systems, mobile phones, personal computers, workstations and game consoles. However, GPUs, or more specifically general-purpose GPUs (GPGPUs), are now also widely used in industrial settings, where growing volumes of data is captured and processed, required by artificial intelligence (AI) and machine learning (ML) platforms and edge-computing systems in automation and IIoT setups.


Handling data Traffic within a CPU moves in a one-way, linear process, so when high volumes of data such as 3D images are involved, bottlenecks occur. GPUs have several cores and enough memory to process some of this data, allowing the CPU to focus on other tasks.


Active Silicon GPU without and with DirectGMA or RDMA


36 November 2022 www.electronicsworld.co.uk


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44