Deep learning recommendation systems must provide high quality, personalized content
under strict tail-latency targets and high system loads. This paper presents RecPipe, a …

Neural personalized recommendation is the cornerstone of a wide collection of cloud
services and products, constituting significant compute demand of cloud infrastructure. Thus …

The development of personalized recommendation has significantly improved the accuracy
of information matching and the revenue of e-commerce platforms. Recently, it has two …

Recommendation systems are of crucial importance for a variety of modern apps and web
services, such as news feeds, social networks, e-commerce, search, etc. To achieve peak …

Deep learning based recommendation systems form the backbone of most personalized
cloud services. Though the computer architecture community has recently started to take …

Industrial recommendation models typically involve numerous feature fields. The embedding
computation workloads are heterogeneous across these fields, thus requiring varied optimal …

Personalized recommendation systems have become one of the most important Internet
services nowadays. A critical challenge of training and deploying the recommendation …

Deep learning-based recommender models (DLRMs) have become an essential component
of many modern recommender systems. Several companies are now building large compute …

Personalized recommendation is an important class of deep-learning applications that
powers a large collection of internet services and consumes a considerable amount of …

Deep Learning Recommendation Models (DLRMs) are very popular in personalized
recommendation systems and are a major contributor to the data-center AI cycles. Due to the …