Nervousness in the CFX user/prospect base due to the Fluent acquisition may require them to reduce prices to maintain sales, but this may be interpreted as an attempt to get what they can for it before it goes end-of-life.

Mixer simulation involving 10 million particles. This type of simulation can greatly benefit from adding GPUs in parallel. (Image courtesy of EDEM.) DEM is a numerical method for computing the motion and effect of a large number of small particles. While it is related to molecular dynamics, the method is generally distinguished by its inclusion of rotational degrees-of-freedom, as well as contact and complicated geometries, including polyhedral.

With advances in computing power and numerical algorithms for nearest neighbor sorting, numerically simulating millions of particles on a single processor is possible. GPUs have become increasingly important for maximizing performance. DEM is regarded as an effective method of addressing engineering problems in granular and discontinuous materials, especially in granular flows and powder mechanics. “Our customers have experienced the value of EDEM simulation across a wide variety of applications,” said Richard LaRoche, EDEM CEO. “As confidence in the method has grown, we are seeing rapidly evolving requirements for applying EDEM to solve many industrial problems involving a large number of fine particles, notably in the powder handling industries such as additive manufacturing. This means it is more important than ever to be able to simulate a large number of particles in a shorter time.

With EDEM 2019, we’re excited to announce a range of capabilities that expand the applications that EDEM can address.” Some of the highlights of the EDEM 2019 release include: • The EDEM multi-GPU solver engine that uses multiple GPU processors to increase the maximum size of simulation can be run on GPUs, which also increases performance. This means users can run large simulations faster.

It also creates more possibilities to run much larger simulations that would not be possible on CPU only. Performance gains from adding a second GPU range between 30 to 90 percent depending on the distribution and size of the simulation. Grecheskij shrift russkij meaning. In general, the larger the simulation (over 1 million particles), the greater the benefit from multi-GPU. The multi-GPU solver is fully double-precision to ensure accuracy and has been developed on OpenCL, providing flexibility for users to use either AMD or NVIDIA graphics cards.