DReAM: An approach to estimate per-Task DRAM energy in multicore systems

Accurate per-task energy estimation in multicore systems would allow performing per-task energy-aware task scheduling and energy-aware billing in data centers, among other applications. Per-task energy estimation is challenged by the interaction between tasks in shared resources, which impacts tasks’ energy consumption in uncontrolled ways. Some accurate mechanisms have been devised recently to estimate per-task energy consumed on-chip in multicores, but there is a lack of such mechanisms for DRAM memories. This article makes the case for accurate per-task DRAM energy metering in multicores, which opens new paths to energy/performance optimizations. In particular, the contributions of this article are (i) an ideal per-task energy metering model for DRAM memories; (ii) DReAM, an accurate yet low cost implementation of the ideal model (less than 5% accuracy error when 16 tasks share memory); and (iii) a comparison with standard methods (even distribution and access-count based) proving that DReAM is much more accurate than these other methods.Peer ReviewedPostprint (author's final draft

MSPlayer: Multi-Source and multi-Path LeverAged YoutubER

Online video streaming through mobile devices has become extremely popular nowadays. YouTube, for example, reported that the percentage of its traffic streaming to mobile devices has soared from 6% to more than 40% over the past two years. Moreover, people are constantly seeking to stream high quality video for better experience while often suffering from limited bandwidth. Thanks to the rapid deployment of content delivery networks (CDNs), popular videos are now replicated at different sites, and users can stream videos from close-by locations with low latencies. As mobile devices nowadays are equipped with multiple wireless interfaces (e.g., WiFi and 3G/4G), aggregating bandwidth for high definition video streaming has become possible. We propose a client-based video streaming solution, MSPlayer, that takes advantage of multiple video sources as well as multiple network paths through different interfaces. MSPlayer reduces start-up latency and provides high quality video streaming and robust data transport in mobile scenarios. We experimentally demonstrate our solution on a testbed and through the YouTube video service.Comment: accepted to ACM CoNEXT'1

Breaking the Barrier Of 2 for the Competitiveness of Longest Queue Drop

We consider the problem of managing the buffer of a shared-memory switch that transmits packets of unit value. A shared-memory switch consists of an input port, a number of output ports, and a buffer with a specific capacity. In each time step, an arbitrary number of packets arrive at the input port, each packet designated for one output port. Each packet is added to the queue of the respective output port. If the total number of packets exceeds the capacity of the buffer, some packets have to be irrevocably rejected. At the end of each time step, each output port transmits a packet in its queue and the goal is to maximize the number of transmitted packets. The Longest Queue Drop (LQD) online algorithm accepts any arriving packet to the buffer. However, if this results in the buffer exceeding its memory capacity, then LQD drops a packet from the back of whichever queue is currently the longest, breaking ties arbitrarily. The LQD algorithm was first introduced in 1991, and is known to be 2-competitive since 2001. Although LQD remains the best known online algorithm for the problem and is of practical interest, determining its true competitiveness is a long-standing open problem. We show that LQD is 1.707-competitive, establishing the first (2-?) upper bound for the competitive ratio of LQD, for a constant ? > 0

Xoncrete: a scheduling tool for partitioned real-time systems

International audienceARINC 653 defines a partitioned framework where the partitions are scheduled according to a predefined cyclic plan and the processes of each partition are scheduled with a fixed priority policy. The timing characteristics defined in ARINC (period and duration) can hardly be used to precisely represent the timing requirements of the applications. We extend the timing model of ARINC 653 to consider deadlines and the periodic behaviour of the individual processes. A novel definition of how to model periodic activities and how this new model is specially useful in an heterogeneous partitioned system is also presented. The new model and the set of scheduling algorithms have been implemented in a scheduling tool (called Xoncrete) to assist the designer to generate the cyclic plan table. Although founded on solid theoretical results, Xoncrete is not a general purpose tool, it is a tool designed to provide real help to the system designer

Analysis of Real-Time Capabilities of Dynamic Scheduled System

This PhD-thesis explores different real-time scheduling approaches to effectively utilize industrial real-time applications on multicore or manycore platforms. The proposed scheduling policy is named the Time-Triggered Constant Phase scheduler for handling periodic tasks, which determines time windows for each computation and communication in advance by using the dependent task model

Center for Aeronautics and Space Information Sciences

This report summarizes the research done during 1991/92 under the Center for Aeronautics and Space Information Science (CASIS) program. The topics covered are computer architecture, networking, and neural nets