Intel has announced that Baidu is architecting the in-memory database of its Feed Stream services to harness the high-capacity and high-performance capabilities of Intel Optane DC persistent memory.
Paired with 2nd Gen Intel Xeon Scalable processors, building a new memory platform based on Intel Optane DC persistent memory allows Baidu to lower its total cost of ownership (TCO) while delivering more personalised search results to users.
“For over 10 years, Intel and Baidu have worked closely together to accelerate Baidu’s core businesses, from search to AI to autonomous driving to cloud services,” says Jason Grebe, Intel corporate vice-president and GM of the cloud platforms and technology group. “Our deep collaboration enables us to rapidly deploy the latest Intel technologies and improve the way customers experience Baidu’s services.”
As companies like Baidu manage the explosive growth of data, the need to quickly and efficiently access and store data is imperative. With today’s news, Baidu is advancing its Feed Stream services to deliver more personalised content to its customers.
Baidu uses an advanced in-memory database called feed-cube to support data storage and information retrieval in its cloud-based Feed Stream services. Deploying Intel Optane DC persistent memory and 2nd Gen Intel Xeon Scalable processors enable Baidu to ensure high concurrency, large capacity and high performance for Feed-Cube, while reducing TCO.
Through close collaboration, Intel and Baidu architected a hybrid memory configuration that includes both Intel Optane DC persistent memory and DRAM within the Baidu Feed Stream services.
With this approach, Feed-Cube saw a boost in search result response times under the pressure of large concurrent access.
At the same time, single-server DRAM usage dropped by more than half, which reduces costs in terms of the petabyte-level storage capacity of Feed-Cube.
“Using Intel Optane DC persistent memory within the Feed-Cube database enables Baidu to cost-effectively scale memory capacity to stay on top of the continuously expanding demands placed on our Feed Stream services,” says Tao Wang, chief architect: recommendation technology architecture at Baidu.