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Benchmarking big data systems: A review
With the fast development of big data systems in recent years, a variety of open-source
benchmarks have been built to evaluate and compare the workloads on these systems, and …
benchmarks have been built to evaluate and compare the workloads on these systems, and …
Auto: Scaling deep reinforcement learning for datacenter-scale automatic traffic optimization
Traffic optimizations (TO, eg flow scheduling, load balancing) in datacenters are difficult
online decision-making problems. Previously, they are done with heuristics relying on …
online decision-making problems. Previously, they are done with heuristics relying on …
Ernest: Efficient performance prediction for {Large-Scale} advanced analytics
Recent workload trends indicate rapid growth in the deployment of machine learning,
genomics and scientific workloads on cloud computing infrastructure. However, efficiently …
genomics and scientific workloads on cloud computing infrastructure. However, efficiently …
Curator:{Self-Managing} Storage for Enterprise Clusters
Modern cluster storage systems perform a variety of background tasks to improve the
performance, availability, durability, and cost-efficiency of stored data. For example, cleaners …
performance, availability, durability, and cost-efficiency of stored data. For example, cleaners …
Detecting anomaly in big data system logs using convolutional neural network
Nowadays, big data systems are being widely adopted by many domains for offering
effective data solutions, such as manufacturing, healthcare, education, and media. Big data …
effective data solutions, such as manufacturing, healthcare, education, and media. Big data …
Making sense of performance in data analytics frameworks
There has been much research devoted to improving the performance of data analytics
frameworks, but comparatively little effort has been spent systematically identifying the …
frameworks, but comparatively little effort has been spent systematically identifying the …
Selecting the best VM across multiple public clouds: a data-driven performance modeling approach
Users of cloud services are presented with a bewildering choice of VM types and the choice
of VM can have significant implications on performance and cost. In this paper we address …
of VM can have significant implications on performance and cost. In this paper we address …
Machine learning for computer systems and networking: A survey
Machine learning (ML) has become the de-facto approach for various scientific domains
such as computer vision and natural language processing. Despite recent breakthroughs …
such as computer vision and natural language processing. Despite recent breakthroughs …
Drizzle: Fast and adaptable stream processing at scale
Large scale streaming systems aim to provide high throughput and low latency. They are
often used to run mission-critical applications, and must be available 24x7. Thus such …
often used to run mission-critical applications, and must be available 24x7. Thus such …
Llama: A heterogeneous & serverless framework for auto-tuning video analytics pipelines
The proliferation of camera-enabled devices and large video repositories has led to a
diverse set of video analytics applications. These applications rely on video pipelines …
diverse set of video analytics applications. These applications rely on video pipelines …