As has been the case for several years, not all computer users need a workstation-class machine, but many do, especially with graphics-oriented and computationally intensive applications, such as MCAD, FEA, and animation. However, high-powered workstations for graphic-intensive applications can come with a price premium. So, you can really pay a relatively high price for higher levels of performance, but is often worth it. There are exceptions, however, and the HP Z2 Mini workstation offers the best of both worlds – a versatile machine with excellent performance at a reasonable price.
I’d classify the HP Z2 Mini as a mid- to high-level machine that provides just about everything most customers would need in a desktop engineering workstation. Then there’s added benefit of the small footprint, which can be huge in a tight work environment.
At software conferences it’s always fun to catch up with old industry acquaintances, but is more interesting to strike up conversations with new companies with innovative ideas. That very thing happened a few weeks ago at SOLIDWORKS World 2017 when we got introduced to Xometry, a company committed to bringing manufacturing back to the U.S. with its software platform for building a reliable and scalable manufacturing program. It employs a unique machine-learning approach that provides its customers with optimal manufacturing capabilities at the best price based on parameters input by customers.
Founded in 2014, Xometry is hoping to transform American manufacturing through a proprietary software platform that provides on-demand manufacturing to a diverse customer base, ranging from startups to Fortune 100 companies. The platform provides an efficient way to source high-quality custom parts, with 24/7 access to instant pricing, expected lead time and manufacturability feedback that recommends best processes and practices. With more than 100 manufacturing partners, the manufacturing capabilities include CNC machining, 3D printing, sheet metal forming and fabrication, and urethane casting with over 200 materials. Xometry’s 4,000+ customers include General Electric, MIT Lincoln Laboratory, NASA, and the United States Army.
While it seems that central processing units (CPUs) get all the glory for computing horsepower, graphical processing units (GPUs) have become the processor of choice for many types of intensively parallel computations.
As the boundaries of computing are pushed in areas such as speech recognition and natural language processing, image and pattern recognition, text and data analytics, and other complex areas, researchers continue to look for new and better ways to extend and expand computing capabilities. For decades this has been accomplished via high-performance computing (HPC) clusters, which use huge amounts of expensive processing power to solve problems.
Researchers at the University of Illinois had studied the possibility of using graphics processing units (GPUs) in desktop supercomputers to speed processing of tasks such as image reconstruction, but it was a computing group at the University of Toronto that demonstrated a way to significantly advance computer vision using GPUs. By plugging in GPUs, previously used primarily for graphics, it became possible to achieve huge performance gains on computing neural networks, and these gains were reflected in superior results in computer vision.
A few weeks ago we were in Los Angeles attending SOLIDWORKS World 2017. As usual, it was an overwhelming whirlwind of people, sights, sounds, and information while it was taking place, but has come into better focus now that some time has transpired for letting all of it sink in and make sense. One of the things I wanted to especially sort out was SOLIDWORKS’ take on model-based definition (MBD), where it stands today, and where it might be headed in the future
The last day of SOLIDWORKS World 2017 I sat down with Oboe Wu, SOLIDWORKS MBD Product Manager, and we discussed several aspects of MBD. Our discussion on SOLIDWORKS MBD centered around the creation and consumption of MBD data (that are tied to customers’ workflows), and the fact that MBD is transitioning from the “why implement” phase to the “how to implement” phase.
In the video below, SOLIDWORKS MBD Product Manager, Oboe Wu, discusses how to eliminate conversion of 3D data to 2D documents and fully leverage 3D design data throughout an organization and partners to reduce redundant tasks. He explains MBD from SOLIDWORKS’ point of view.
Since it began in 1986, Spatial has developed software components – modular software packages that perform a set of specific and related functions. This class of software is designed to work as a functional component of a larger application, such as CAD, CAM, CAE, Additive Manufacturing (AM), and Building Information Modeling (BIM). The goal of component software is to standardize the interfaces between software utility functions so that they can work together efficiently and cohesively.
In developing its software components, Spatial has always realized, too, that the best engineering software excels at optimizing imported data for data reuse. Spatial understands that design data reuse is much more than just data exchange.