Imaging's Matrox Supersight
is designed for imaging applications with a high throughput. Leveraging
multiple clusters of CPUs, GPUs and FPGAs, Matrox Supersight e2 provides an
environment for considerable data and task-level parallel processing through a
PCI Express x16 2.0 (Gen2) switch fabric. The Matrox Imaging Library, which
includes its Distributed MIL API, allows developers to create applications for
Matrox Supersight e2. As MIL is supported on all Matrox Imaging hardware
platforms, development on Matrox Supersight e2 is simplified and ensures that
the source code is portable across all devices, from nodes with 48 CPU cores
and 4 FPGAs, to a node with 12 CPU cores, 1 FPGA and 6 (double-wide) GPUs, and
everything in between. A high-bandwidth PCIe 2.0 switched fabric backplane, provides
substantial data throughput and expansion capability for supporting up to six
double-wide or up to nine single-wide GPUs in a 4U platform. Each ATI FirePro
Professional Graphics card provides up to 1600 stream processors and 147.2 GB/s
of memory bandwidth.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
Using Siemens NX software, a team of engineering students from the University of Michigan built an electric vehicle and raced in the 2013 Bridgestone World Solar Challenge. One of those students blogged for Design News throughout the race.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.