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Pond: Cxl-based memory pooling systems for cloud platforms
Public cloud providers seek to meet stringent performance requirements and low hardware
cost. A key driver of performance and cost is main memory. Memory pooling promises to …
cost. A key driver of performance and cost is main memory. Memory pooling promises to …
{MLaaS} in the wild: Workload analysis and scheduling in {Large-Scale} heterogeneous {GPU} clusters
With the sustained technological advances in machine learning (ML) and the availability of
massive datasets recently, tech companies are deploying large ML-as-a-Service (MLaaS) …
massive datasets recently, tech companies are deploying large ML-as-a-Service (MLaaS) …
Llumnix: Dynamic scheduling for large language model serving
Inference serving for large language models (LLMs) is the key to unleashing their potential
in people's daily lives. However, efficient LLM serving remains challenging today because …
in people's daily lives. However, efficient LLM serving remains challenging today because …
An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems
Cloud services have recently started undergoing a major shift from monolithic applications,
to graphs of hundreds or thousands of loosely-coupled microservices. Microservices …
to graphs of hundreds or thousands of loosely-coupled microservices. Microservices …
Learning scheduling algorithms for data processing clusters
Efficiently scheduling data processing jobs on distributed compute clusters requires complex
algorithms. Current systems use simple, generalized heuristics and ignore workload …
algorithms. Current systems use simple, generalized heuristics and ignore workload …
{FIRM}: An intelligent fine-grained resource management framework for {SLO-Oriented} microservices
User-facing latency-sensitive web services include numerous distributed,
intercommunicating microservices that promise to simplify software development and …
intercommunicating microservices that promise to simplify software development and …
A closer look at spatiotemporal convolutions for action recognition
In this paper we discuss several forms of spatiotemporal convolutions for video analysis and
study their effects on action recognition. Our motivation stems from the observation that 2D …
study their effects on action recognition. Our motivation stems from the observation that 2D …
Cluster resource scheduling in cloud computing: literature review and research challenges
Scheduling plays a pivotal role in cloud computing systems. Designing an efficient
scheduler is a challenging task. The challenge comes from several aspects, including the …
scheduler is a challenging task. The challenge comes from several aspects, including the …
Who limits the resource efficiency of my datacenter: An analysis of alibaba datacenter traces
Cloud platform provides great flexibility and cost-efficiency for end-users and cloud
operators. However, low resource utilization in modern datacenters brings huge wastes of …
operators. However, low resource utilization in modern datacenters brings huge wastes of …
Sinan: ML-based and QoS-aware resource management for cloud microservices
Cloud applications are increasingly shifting from large monolithic services, to large numbers
of loosely-coupled, specialized microservices. Despite their advantages in terms of …
of loosely-coupled, specialized microservices. Despite their advantages in terms of …