Driven by Big Data and new applications, modern servers and data centers are out of synch with current demands – due to increasing requirements for real-time access to large amounts of information.
That is precisely why Rambus’ Smart Data Acceleration (SDA) research program focuses on architectures designed to offload computing closer to very large data sets at multiple points in the memory and storage hierarchy.
Comprising software, firmware, FPGAs and large amounts of memory, the platform is designed to test new methods of optimizing and accelerating data analytics for extremely large data sets. Potential use case scenarios include real-time risk analytics, ad serving, neural imaging, transcoding and genome mapping.
As we’ve previously discussed on Rambus Press, data centers have traditionally focused on raw compute, causing power and cooling costs to skyrocket. An alternative paradigm, says Rambus VP of solutions marketing Steve Woo, is to continue trending towards the design of modular resources with varying levels of processing, memory, bandwidth, capacity and storage.
“Modular, disaggregated architectures allow resources to be provided and assigned as needed to meet the widely varying demands of modern workloads. For example, serving up basic webpages and streaming YouTube videos can be achieved on an individual server with modest compute and memory resources,” he continued. “However, heavy analytics jobs or scientific computing tasks that process gigabytes of user or machine data require much higher compute, memory and storage capabilities and often entail many resources working together.”
As Woo emphasizes, a modular, disaggregated approach to data centers can help balance the ever-increasing requirements of Big Data and multiple core counts with accelerated demands for memory, storage capacity and bandwidth.
“Without a parallel boost in bandwidth and capacity, data centers won’t be able to take advantage of increasing CPU core counts,” he added. “Simply put, the key to building the data center of the future is providing a healthy balance between compute, memory and storage. The flexibility afforded by disaggregating resources is a compelling way to meet the needs of modern workloads.”