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  1. AU="Przybylski, Bartłomiej"
  2. AU="Lisda Amalia" AU="Lisda Amalia"
  3. AU="Ahmed S.M. Al-Janabi"
  4. AU="Yamaguchi, Hiromi"
  5. AU="Boyatzis, Chris J"

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  1. Book ; Online: Call Scheduling to Reduce Response Time of a FaaS System

    Żuk, Paweł / Przybylski, Bartłomiej / Rzadca, Krzysztof

    2022  

    Abstract: In an overloaded FaaS cluster, individual worker nodes strain under lengthening queues of requests. Although the cluster might be eventually horizontally-scaled, adding a new node takes dozens of seconds. As serving applications are tuned for tail ... ...

    Abstract In an overloaded FaaS cluster, individual worker nodes strain under lengthening queues of requests. Although the cluster might be eventually horizontally-scaled, adding a new node takes dozens of seconds. As serving applications are tuned for tail serving latencies, and these greatly increase under heavier loads, the current workaround is resource over-provisioning. In fact, even though a service can withstand a steady load of, e.g., 70% CPU utilization, the autoscaler is triggered at, e.g., 30-40% (thus the service uses twice as many nodes as it would be needed). We propose an alternative: a worker-level method handling heavy load without increasing the number of nodes. FaaS executions are not interactive, compared to, e.g., text editors: end-users do not benefit from the CPU allocated to processes often, yet for short periods. Inspired by scheduling methods for High Performance Computing, we take a radical step of replacing the classic OS preemption by (1) queuing requests based on their historical characteristics; (2) once a request is being processed, setting its CPU limit to exactly one core (with no CPU oversubscription). We extend OpenWhisk and measure the efficiency of the proposed solutions using the SeBS benchmark. In a loaded system, our method decreases the average response time by a factor of 4. The improvement is even higher for shorter requests, as the average stretch is decreased by a factor of 18. This leads us to show that we can provide better response-time statistics with 3 machines compared to a 4-machine baseline.
    Keywords Computer Science - Distributed ; Parallel ; and Cluster Computing
    Subject code 000
    Publishing date 2022-07-26
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  2. Book ; Online: Divide (CPU Load) and Conquer

    Przybylski, Bartłomiej / Żuk, Paweł / Rzadca, Krzysztof

    Semi-Flexible Cloud Resource Allocation

    2022  

    Abstract: Cloud resource management is often modeled by two-dimensional bin packing with a set of items that correspond to tasks having fixed CPU and memory requirements. However, applications running in clouds are much more flexible: modern frameworks allow to ( ... ...

    Abstract Cloud resource management is often modeled by two-dimensional bin packing with a set of items that correspond to tasks having fixed CPU and memory requirements. However, applications running in clouds are much more flexible: modern frameworks allow to (horizontally) scale a single application to dozens, even hundreds of instances; and then the load balancer can precisely divide the workload between them. We analyze a model that captures this (semi)-flexibility of cloud resource management. Each cloud application is characterized by its memory footprint and its momentary CPU load. Combining the scheduler and the load balancer, the resource manager decides how many instances of each application will be created and how the CPU load will be balanced between them. In contrast to the divisible load model, each instance of the application requires a certain amount of memory, independent of the number of instances. Thus, the resource manager effectively trades additional memory for more evenly balanced load. We study two objectives: the bin-packing-like minimization of the number of machines used; and the makespan-like minimization of the maximum load among all the machines. We prove NP-hardness of the general problems, but also propose polynomial-time exact algorithms for boundary special cases. Notably, we show that (semi)-flexibility may result in reducing the required number of machines by a tight factor of $2-\varepsilon$. For the general case, we propose heuristics that we validate by simulation on instances derived from the Azure trace.
    Keywords Computer Science - Distributed ; Parallel ; and Cluster Computing
    Subject code 004
    Publishing date 2022-06-10
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  3. Book ; Online: Scheduling.jl -- Collaborative and Reproducible Scheduling Research with Julia

    Hunold, Sascha / Przybylski, Bartłomiej

    2020  

    Abstract: We introduce the Scheduling.jl Julia package, which is intended for collaboratively conducting scheduling research and for sharing implementations of algorithms. It provides the fundamental building blocks for implementing scheduling algorithms following ...

    Abstract We introduce the Scheduling.jl Julia package, which is intended for collaboratively conducting scheduling research and for sharing implementations of algorithms. It provides the fundamental building blocks for implementing scheduling algorithms following the three-field notation of Graham et al., i.e., it has functionality to describe machine environments, job characteristics, and optimality criteria. Our goal is to foster algorithm and code sharing in the scheduling community. Scheduling.jl can also be used to support teaching scheduling theory in classes. We will show the main functionalities of Scheduling.jl and give an example on how to use it by comparing different algorithms for the problem of P||Cmax .

    Comment: 5 pages, 1 figure, 2 listings
    Keywords Computer Science - Data Structures and Algorithms
    Publishing date 2020-03-11
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  4. Book ; Online: Data-driven scheduling in serverless computing to reduce response time

    Przybylski, Bartłomiej / Żuk, Paweł / Rzadca, Krzysztof

    2021  

    Abstract: In Function as a Service (FaaS), a serverless computing variant, customers deploy functions instead of complete virtual machines or Linux containers. It is the cloud provider who maintains the runtime environment for these functions. FaaS products are ... ...

    Abstract In Function as a Service (FaaS), a serverless computing variant, customers deploy functions instead of complete virtual machines or Linux containers. It is the cloud provider who maintains the runtime environment for these functions. FaaS products are offered by all major cloud providers (e.g. Amazon Lambda, Google Cloud Functions, Azure Functions); as well as standalone open-source software (e.g. Apache OpenWhisk) with their commercial variants (e.g. Adobe I/O Runtime or IBM Cloud Functions). We take the bottom-up perspective of a single node in a FaaS cluster. We assume that all the execution environments for a set of functions assigned to this node have been already installed. Our goal is to schedule individual invocations of functions, passed by a load balancer, to minimize performance metrics related to response time. Deployed functions are usually executed repeatedly in response to multiple invocations made by end-users. Thus, our scheduling decisions are based on the information gathered locally: the recorded call frequencies and execution times. We propose a number of heuristics, and we also adapt some theoretically-grounded ones like SEPT or SERPT. Our simulations use a recently-published Azure Functions Trace. We show that, compared to the baseline FIFO or round-robin, our data-driven scheduling decisions significantly improve the performance.
    Keywords Computer Science - Distributed ; Parallel ; and Cluster Computing
    Subject code 000
    Publishing date 2021-05-07
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  5. Book ; Online: A log-linear $(2+5/6)$-approximation algorithm for parallel machine scheduling with a single orthogonal resource

    Naruszko, Adrian / Przybylski, Bartłomiej / Rzadca, Krzysztof

    2021  

    Abstract: As the gap between compute and I/O performance tends to grow, modern High-Performance Computing (HPC) architectures include a new resource type: an intermediate persistent fast memory layer, called burst buffers. This is just one of many kinds of ... ...

    Abstract As the gap between compute and I/O performance tends to grow, modern High-Performance Computing (HPC) architectures include a new resource type: an intermediate persistent fast memory layer, called burst buffers. This is just one of many kinds of renewable resources which are orthogonal to the processors themselves, such as network bandwidth or software licenses. Ignoring orthogonal resources while making scheduling decisions just for processors may lead to unplanned delays of jobs of which resource requirements cannot be immediately satisfied. We focus on a classic problem of makespan minimization for parallel-machine scheduling of independent sequential jobs with additional requirements on the amount of a single renewable orthogonal resource. We present an easily-implementable log-linear algorithm that we prove is $2\frac56$-approximation. In simulation experiments, we compare our algorithm to standard greedy list-scheduling heuristics and show that, compared to LPT, resource-based algorithms generate significantly shorter schedules.
    Keywords Computer Science - Distributed ; Parallel ; and Cluster Computing
    Subject code 006 ; 000
    Publishing date 2021-08-31
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

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  6. Book ; Online: Using Unused

    Przybylski, Bartłomiej / Pawlik, Maciej / Żuk, Paweł / Łagosz, Bartłomiej / Malawski, Maciej / Rzadca, Krzysztof

    Non-Invasive Dynamic FaaS Infrastructure with HPC-Whisk

    2022  

    Abstract: Modern HPC workload managers and their careful tuning contribute to the high utilization of HPC clusters. However, due to inevitable uncertainty it is impossible to completely avoid node idleness. Although such idle slots are usually too short for any ... ...

    Abstract Modern HPC workload managers and their careful tuning contribute to the high utilization of HPC clusters. However, due to inevitable uncertainty it is impossible to completely avoid node idleness. Although such idle slots are usually too short for any HPC job, they are too long to ignore them. Function-as-a-Service (FaaS) paradigm promisingly fills this gap, and can be a good match, as typical FaaS functions last seconds, not hours. Here we show how to build a FaaS infrastructure on idle nodes in an HPC cluster in such a way that it does not affect the performance of the HPC jobs significantly. We dynamically adapt to a changing set of idle physical machines, by integrating open-source software Slurm and OpenWhisk. We designed and implemented a prototype solution that allowed us to cover up to 90\% of the idle time slots on a 50k-core cluster that runs production workloads.
    Keywords Computer Science - Distributed ; Parallel ; and Cluster Computing
    Subject code 000
    Publishing date 2022-11-01
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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