Electronic Design Automation Industry

Engaging Electronic Design Automation

Electronic Design Automation (EDA) has benefited over the years as the speed and complexity of the CPU increased. The requirement of customers to demand ever faster systems to squeeze every possible clock cycle out of chip design simulations is something that Cirrascale has had a lot of experience. EDA simulations require the highest wattage, fastest clock speed CPUs and need them delivered at the highest densities possible. This is available from the BladeRack 2 platform.

Over 1100 CPU compute threads in one rack are ready to tackle the toughest datasets. EDA also requires fast access to storage, with Cirrascale's server and storage architecture; you can have both in the same high density package. If your applications can be parallelized to the extreme, then you need to consider using GPU acceleration to bring about another leap in processing power. Utilizing Cirrascale's GB5400/GB5600 Series of advanced GPU compute servers, customers can place up to 96 NVIDIA® Tesla® K80 Dual-GPU Accelerator in a single rack for some serious GPU compute power.

Featured Resources for Electronic Design Automation

Electronic Design for High Performance Computations

The EDA industry's reliance on High Performance Computing has revolutionized the search for newer and better ways for CPUs, GPUs, memory, and networking technologies to advance, grow, and converge. For Electronic Design companies relying on ultimate flexibility in the design of their compute systems, each new creation of even more powerful technological innovations are brought to market in a Cirrascale compute blade server as quickly as possible utilizing the BladeRack 2 FL platform.

Download EDA BladeRack 2 FL Data Sheet
Scaling GPU Compute Performance White Paper

GPU chip manufacturers have been providing more computational power within each GPU card. Recently, this includes packing multiple GPUs within each card, such as the NVIDIA® Tesla® K80 Dual-GPU Accelerator cards, which contain two GPUs per card. Additionally, with new iterations, they continue to increase overall memory size and bandwidth accessible to those GPUs to accelerate multiple HPC applications. Read this paper to discover the best way to scale GPU compute performance.

Download Cirrascale GPU Compute Performance White Paper
NVIDIA® GPU Application Catalog

NVIDIA identifies over two hundred applications for a wide range of industries already optimized for GPUs, including High Performance Computing. Discover if your application is supported and put those applications to work with a Cirrascale GB series blade server.

Download NVIDIA® GPU Application Catalog

Share This Page:  

©2017. All Rights Reserved. Cirrascale Corporation..