Adaptable, accelerated & amplified
What is Accelerated Computing?
Accelerated computing is a modern style of computing that separates the data-intensive parts of an application and processes them on a separate acceleration device, leaving the control functionality to be processed on the CPU. This allows demanding applications to run more quickly and efficiently as the underlying processor hardware is more efficient for the type of processing needed. Having separate types of hardware processors, including accelerators, is known as heterogeneous computing because there are multiple types of compute resources available for the application to utilize.
Typically, hardware accelerators have a parallel processing structure that allows them to perform tasks simultaneously, instead of in a linear or serial fashion. As such, they’re able to optimize the intensive data-plane processing portions of applications while the CPU continues to run control-plane code that cannot be run in parallel. The result is efficient, high-performance computing.
Up to 90X higher performance than CPUs on key workloads at one-third the cost
Over 4X higher inference throughput and 3X latency advantage over GPU-based solutions
Accelerate Any Workload
Machine learning inference to video processing to any workload using the same accelerator card
As workload algorithms evolve, use reconfigurable hardware to adapt faster than fixed-function accelerator card product cycles
Cloud to On-Premises Mobility
Deploy solutions in the cloud or on-premises interchangeably, scalable to application requirements
Applications available for common workloads, or build your own with the Application Developer Tool
Acceleration for dynamic workloads
Data Center accelerator cards provide optimized acceleration for workloads in financial computing, machine learning, computational storage, and data search and analytics. Accelerator cards are designed to meet the constantly changing needs of the modern Data Center, providing higher performance than CPUs and GPUs for key workloads, including machine learning inference, video transcoding, and database search & analytics. Designed to meet the constantly changing needs of the modern Data Center, providing higher performance than CPUs and GPUs for key workloads, including machine learning inference, video transcoding, and database search & analytics.