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Cryptocurrency mining can be said to be the modern alchemy, involving as it does the transmutation of electricity into digital gold. The goal of mining is to guess the solution to a cryptographic puzzle, the difficulty of which is determined by the network, and thence to win the block reward and transaction fees. Because the return on solo mining has a very high variance, miners band together to create...
The programmability of Software-Defined Networking (SDN) challenges the correctness and reliability of networks. There may be design flaws as well as implementation bugs in SDN applications. White-box testing methods with formal models rely on source codes, which limits the applicability of these methods. Black-box methods without behavior models cannot systematically cover an application's functions...
In this paper we study how to estimate the back-off rates in an idealized CSMA network consisting of n links to achieve a given throughput vector using free energy approximations. More specifically, we introduce the class of region-based free energy approximations with clique belief and present a closed form expression for the back-off rates based on the zero gradient points of the free energy approximation...
Software systems with quality of service (QoS), such as database management systems and web servers, are ubiquitous. Such systems must meet strict performance requirements. Instrumentation is a useful technique for the analysis and debugging of QoS systems. Dynamic binary instrumentation (DBI) extracts runtime information to comprehend system's behavior and detect performance bottlenecks. However,...
Conventional system simulators are readily used by computer architects to design and evaluate their processor designs. These simulators provide reasonable levels of accuracy and execution detail but suffer from long simulation latencies and increased implementation complexity. In this work we propose iQ, a queue-based modeling technique that targets design space exploration and optimization studies...
Advanced computer security systems rely on a host of detectors that examine anomalies, or known signatures, to qualify network traffic. Anomaly detectors usually come at greater cost in resources over signature detectors spurring the desire to translate anomalies into identifiable signatures. Automatic Signature Generation (ASG) attempts to automate the process of creating signatures to describe newly...
The accurate measurement of a server's power consumption when running realistic workloads enables characterization of its energy efficiency and helps to make better provisioning and workload placement decisions. Information on the energy efficiency of a server for a given target workload can greatly influence such decisions and thus the final energy efficiency of a cluster or data center. However,...
A datacenter's power consumption is a major contributor to its operational expenditures (op-ex) and one-time capital expenditures (cap-ex). The recurring electricity cost is often in large determined by datacenter peak-demand under peak-based pricing which is employed by major electric utility providers. There is a growing interest in reducing a datacenter's electricity costs by using throttling techniques...
Demand response refers to reducing energy consumption of participating systems in response to transient surge in power demand or other emergency events. Demand response is particularly important for maintaining power grid transmission stability, as well as achieving overall energy saving. High Performance Computing (HPC) systems can be considered as ideal participants for demand-response programs,...
Die-stacked DRAM (a.k.a., on-chip DRAM) provides much higher bandwidth and lower latency than off-chip DRAM. It is a promising technology to break the "memory wall". Die-stacked DRAM can be used either as a cache (i.e., DRAM cache) or as a part of memory (PoM). A DRAM cache design would suffer from more page faults than a PoM design as the DRAM cache cannot contribute towards capacity of...
Increasing data set sizes motivate for a shift of focus from computation-centric systems to data-centric systems, where data movement is treated as a first-class optimization metric. An example of this emerging paradigm is in-situ computing in largescale computing systems. Observing that data movement costs are increasing at an exponential rate even at a node level (as a node itself is fast-becoming...
Since main memory system contributes to a large and increasing fraction of server/datacenter energy consumption, there have been several efforts to reduce its power and energy consumption. DVFS schemes have been used to reduce the memory power, but they come with a performance penalty. In this work, we propose DEMM, an OS-based, high performance DVFS mechanism that reduces memory power by dynamically...
This paper investigates the problem of deriving a white box performance model of Hardware Transactional Memory (HTM) systems. The proposed model targets TSX, a popular implementation of HTM integrated in Intel processors starting with the Haswell family in 2013.An inherent difficulty with building white-box models of commercially available HTM systems is that their internals are either vaguely documented...
One of the key performance challenges in cloud computing is the problem of interference, or resource contention, among colocated VMs. While prior work has empirically analyzed interference for specific workloads under specific settings, there is a need for a generic approach to estimate application performance under any interference condition.In this paper, we present an analytical model to estimate...
A significant fraction of the operational expenditures incurred by cloud service providers relates to their networking (Internet access) and electricity consumption. Both depend on the peak-demand over the billing interval. In the future, cloud services providers may in turn recoup these costs from their long-term customers through peak-based pricing. We explore two different methods for the cloud...
In this paper we evaluate a measurement-based approach to performance prediction of data-intensive applications over NoSQL systems. While the use of systematic measurements for building performance prediction models is a well studied topic, little attention has been paid so far on the application space of data-intensive systems using NoSQL databases. Measurement-based performance prediction approaches...
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