Related papers: Lovelock: Towards Smart NIC-hosted Clusters
Design and architecture of cloud storage system plays a vital role in cloud computing infrastructure in order to improve the storage capacity as well as cost effectiveness. Usually cloud storage system provides users to efficient storage…
Huge energy consumption poses a significant challenge for edge clouds. In response to this, we introduce a new type of edge server, namely SoC Cluster, that orchestrates multiple low-power mobile system-on-chips (SoCs) through an on-chip…
Today's datacenter applications rely on datastores that are required to provide high availability, consistency, and performance. To achieve high availability, these datastores replicate data across several nodes. Such replication is managed…
We present FLIC, a distributed software data caching framework for fogs that reduces network traffic and latency. FLICis targeted toward city-scale deployments of cooperative IoT devices in which each node gathers and shares data with…
Recent trends see a move away from a fixed-resource server-centric datacenter model to a more adaptable "disaggregated" datacenter model. These disaggregated datacenters can then dynamically group resources to the specific requirements of…
Distributed dataflow systems such as Apache Spark or Apache Flink enable parallel, in-memory data processing on large clusters of commodity hardware. Consequently, the appropriate amount of memory to allocate to the cluster is a crucial…
The trend toward specialized processing devices such as TPUs, DPUs, GPUs, and FPGAs has exposed the weaknesses of PCIe in interconnecting these devices and their hosts. Several attempts have been proposed to improve, augment, or downright…
The increasing prominence of AI necessitates the deployment of inference platforms for efficient and effective management of AI pipelines and compute resources. As these pipelines grow in complexity, the demand for distributed serving rises…
The under exploitation of the available resources risks to be one of the main problems for a computing center. The growing demand of computational power necessarily entails more complex approaches in the management of the computing…
Disaggregated memory is a promising approach that addresses the limitations of traditional memory architectures by enabling memory to be decoupled from compute nodes and shared across a data center. Cloud platforms have deployed such…
Systolic arrays and shared-L1-memory manycore clusters are commonly used architectural paradigms that offer different trade-offs to accelerate parallel workloads. While the first excel with regular dataflow at the cost of rigid…
Despite the de-facto technological uniformity fostered by the cloud and edge computing paradigms, resource fragmentation across isolated clusters hinders the dynamism in application placement, leading to suboptimal performance and…
Traditional Artificial Cognitive Systems (for example, intelligent robots) share a number of limitations. First, they are usually made up only of machine components; humans are only playing the role of user or supervisor. And yet, there are…
The rapid growth of data-intensive applications such as generative AI, scientific simulations, and large-scale analytics is driving modern supercomputers and data centers toward increasingly heterogeneous and tightly integrated…
Performing analytic of household load curves (LCs) has significant value in predicting individual electricity consumption patterns, and hence facilitate developing demand-response strategy, and finally achieve energy efficiency improvement…
While (1) serverless computing is emerging as a popular form of cloud execution, datacenters are going through major changes: (2) storage dissaggregation in the system infrastructure level and (3) integration of domain-specific accelerators…
The emergence of new, off-path smart network cards (SmartNICs), known generally as Data Processing Units (DPU), has opened a wide range of research opportunities. Of particular interest is the use of these and related devices in tandem with…
Memory disaggregation is being considered as a strong alternative to traditional architecture to deal with the memory under-utilization in data centers. Disaggregated memory can adapt to dynamically changing memory requirements for the data…
The recent growth of Artificial Intelligence (AI), particularly large language models, requires energy-demanding high-performance computing (HPC) data centers, which poses a significant burden on power system capacity. Scheduling data…
The current trend in end-user devices' advancements in computing and communication capabilities makes edge computing an attractive solution to pave the way for the coveted ultra-low latency services. The success of the edge computing…