Power-Aware Allocation of Graph Jobs in Geo-Distributed Cloud Networks
In the era of big-data, the jobs submitted to the clouds exhibit complicated structures represented by graphs, where the nodes denote the sub-tasks each of which can be accommodated at a <italic>slot</italic> in a server, while the edges indicate the ...
cCUDA: Effective Co-Scheduling of Concurrent Kernels on GPUs
While GPUs are meantime omnipresent for many scientific and technical computations, they still continue to evolve as processors. An important recent feature is the ability to execute multiple kernels concurrently via queue streams. However, experiments ...
Hotspot-Aware Hybrid Memory Management for In-Memory Key-Value Stores
Emerging Non-Volatile Memory (NVM) technologies promise much higher memory density and energy efficiency than DRAM, at the expense of higher read/write latency and limited write endurance. Hybrid memory systems composed of DRAM and NVM have the potential ...
Resource-Constrained Replication Strategies for Hierarchical and Heterogeneous Tasks
In large-scale cloud computing systems, a task is often divided into multiple subtasks which can be executed in parallel in different machines. As a result, the task completion time is constrained by the completion time of the slowest subtask. To reduce ...
Quantum Supremacy Circuit Simulation on Sunway TaihuLight
With the rapid progress made by industry and academia, quantum computers with dozens of qubits or even larger size are being realized. However, the fidelity of existing quantum computers often sharply decreases as the circuit depth increases. Thus, an ...
On Fault-Tolerant Bin Packing for Online Resource Allocation
We study an online fault-tolerant bin packing problem that models reliable resource allocation. In this problem, each item is replicated and has <inline-formula><tex-math notation="LaTeX">$f+1$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>f</mml:mi>...
A Holistic Heterogeneity-Aware Data Placement Scheme for Hybrid Parallel I/O Systems
We present <sc>H2DP</sc>, a holistic heterogeneity-aware data placement scheme for hybrid parallel I/O systems, which consist of HDD servers and SSD servers. Most of the existing approaches focus on server performance or application I/O pattern ...
gQoS: A QoS-Oriented GPU Virtualization with Adaptive Capacity Sharing
Currently, the virtualization technologies for cloud computing infrastructures supporting extra devices, such as GPU, require additional development and refinement. This requirement is particularly evident in the area of resource sharing and allocation ...
A Novel Multi-Stage Forest-Based Key-Value Store for Holistic Performance Improvement
Key-value (KV) stores based on multi-stage structures are widely deployed to organize massive amounts of easily searchable user data. However, current KV storage systems inevitably sacrifice at least one of the performance objectives, such as write, read, ...
Reliability Aware Energy Optimized Scheduling of Non-Preemptive Periodic Real-Time Tasks on Heterogeneous Multiprocessor System
Higher reliability and lower energy consumption are conflicting, yet among the most important design objectives for the real-time systems. Moreover, in the domain of real-time systems, non-preemptive scheduling is relatively unexplored with objectives ...
Combining Size-Based Load Balancing with Round-Robin for Scalable Low Latency
When dispatching jobs to parallel servers, or queues, the highly scalable round-robin (RR) scheme reduces the variance of interarrival times at all queues to a great extent but has no impact on the variances of service processes. Contrariwise, size-...
HRHS: A High-Performance Real-Time Hardware Scheduler
This article represents an on-line time-predictable distributed hardware scheduler solution, suitable for many-core systems. We have partitioned the Main scheduler into uniform Partial schedulers to achieve a significant gain in term of performance and ...
Energy-Aware Application Placement in Mobile Edge Computing: A Stochastic Optimization Approach
The Quality of Service (QoS) in Mobile Edge Computing (MEC) systems is significantly dependent on the application offloading and placement decisions. Due to the movement of users in MEC networks, an optimal application placement might turn into the least ...
Towards Accurate Prediction for High-Dimensional and Highly-Variable Cloud Workloads with Deep Learning
Resource provisioning for cloud computing necessitates the adaptive and accurate prediction of cloud workloads. However, the existing methods cannot effectively predict the high-dimensional and highly-variable cloud workloads. This results in resource ...
Efficient Method for Parallel Computation of Geodesic Transformation on CPU
This article introduces a fast Central Processing Unit (CPU) implementation of geodesic morphological operations using stream processing. In contrast to the current state-of-the-art, that focuses on achieving insensitivity to the filter sizes with ...
Online Placement and Scaling of Geo-Distributed Machine Learning Jobs via Volume-Discounting Brokerage
Geo-distributed machine learning (ML) often uses large geo-dispersed data collections produced over time to train global models, without consolidating the data to a central site. In the parameter server architecture, “workers” and “...
COPA: Highly Cost-Effective Power Back-Up for Green Datacenters
Traditional datacenters employ costly diesel generators (DG) and uninterrupted power supplies (UPS) to back up power. However, some or even all racks of a <italic>green</italic> datacenter can still be powered by renewable energy during grid power ...
Towards Power Efficient High Performance Packet I/O
Recently, high performance packet I/O frameworks continue to flourish for their ability to process packets from high-speed links. To achieve high throughput and low latency, high performance packet I/O frameworks usually employ busy polling. As busy ...