5351237
Game traffic analysis: an MMORPG perspective
Online gaming is one of the most profitable businesses over the Internet. Among all genres of the online games, the popularity of the MMORPG (Massive Multiplayer Online Role Playing Games) is especially prominent in Asia. Opting for a better understanding of the game traffic and the economic well being of the Internet, we analyze a 1,356-million-packet trace from a sizeable MMORPG, ShenZhou Online. This work is, as far as we know, the first formal analysis on the MMORPG server traces.We find that the MMORPG and FPS (First-Person Shooting) games are similar in that they both generate small packets and require low bandwidths. In particular, the bandwidth requirement of MMORPG is even lower due to the less real-time game play. More distinctive are the strong periodicity, temporal locality, and irregularity observed in the MMORPG traffic. The periodicity is due to a common practice in game implementation, where the game state updates are accumulated within a fixed time window before transmission. The temporal locality in the game traffic is largely due to the game nature where one action leads to another. The irregularity, particular unique in MMORPG traffic, is due to the diversity of game design where the user behavior can be drastically different depending on the quest at hand.
195352079
The impact of network variabilities on TCP clocking schemes
10023746
Test and diagnosis of word-oriented multiport memories
Conventionally, the test of multiport memories is considered difficult because of the complex behavior of the faulty memories and the large number of inter-port faults. This paper presents an efficient approach for testing and diagnosing multiport RAMs. Our approach takes advantage of the higher access bandwidth due to the increased number of read/write ports, which also provides higher observability and controllability that effectively reduces the test time. Our key idea is that a sequence of March operations for any memory cell can be folded and executed within a single access cycle. We have also developed an efficient test algorithm for port-specific faults as well as traditional cell faults. The port-specific faults include the stuck-open, address decoder, and inter-port faults, for both bit-oriented and word-oriented RAMs. Experimental results for our folding scheme show that the test time reduction is about 28% for a commercial 8 KB embedded SRAM. An efficient diagnostic algorithm is also proposed for the port-specific faults and traditional cell faults.
6505998
Failure factor based yield enhancement for SRAM designs
With increasing chip density, semiconductor memory yield improvement is becoming a task that can only be done collaboratively by test engineers, product engineers, process engineers, and circuit designers. Design-for-manufacturability (DFM) and design-for-yield (DFY) methodologies have an increasing impact on the yield learning of modem silicon chips. However, a major part of a system chip is typically occupied by memories, which dominate the yield of the chip. During chip integration, it is important that we pick the right design of memory cores that will maximize the yield under the specific process technology chosen. Traditionally, yield prediction is only based on layout and defect statistics. In this paper, we propose to estimate the yield with a failure factor. We thus develop a memory failure factor analyzer (FFA), based on that, we can select the memory design that is more suitable for the given process technology. Experimental results show that we can efficiently evaluate the yields of different memory designs for the same specification, so that the most robust one, that results in the highest yield, can be selected.
2158099
Keyphrase Extraction Using Semantic Networks Structure Analysis
Keyphrases play a key role in text indexing, summarization and categorization. However, most of the existing keyphrase extraction approaches require human-labeled training sets. In this paper, we propose an automatic keyphrase extraction algorithm, which can be used in both supervised and unsupervised tasks. This algorithm treats each document as a semantic network. Structural dynamics of the network are used to extract keyphrases (key nodes) unsupervised. Experiments demonstrate the proposed algorithm averagely improves 50% in effectiveness and 30% in efficiency in unsupervised tasks and performs comparatively with supervised extractors. Moreover, by applying this algorithm to supervised tasks, we develop a classifier with an overall accuracy up to 80%.
54735
An architecture for real-time active content distribution
The phenomenal growth of the World Wide Web has made it the most popular Internet application today. Web caching and content distribution services have been recognized as valuable techniques to mitigate the explosion of Web traffic. An increasing fraction of Web traffic today is dynamically generated and therefore intrinsically difficult for replication using present static approaches. Scalable delivery of such active content poses a myriad of challenges, including content replication, update propagation, and consistency management. This paper makes two contributions: (1) it describes a scalable architecture for transparent demand-driven distribution of active content; (2) the system can provide real-time delay guarantee on content access. Our approach involves migrating the scripts which generate the dynamic Web traffic, and their data, from the server to active content distribution proxies nearest to the clients and mechanisms on these proxies to enforce real-time delay guarantees for client requests. Our system is implemented and deployed on PlanetLab, a real-world distributed Internet testbed. Experimental data show that significant improvements are observed in effective throughput and client response time, and delay bounds on content access can be guaranteed with a very high probability.
7537228
Achieving strong scaling with NAMD on Blue Gene/L
NAMD is a scalable molecular dynamics application, which has demonstrated its performance on several parallel computer architectures. Strong scaling is necessary for molecular dynamics as problem size is fixed, and a large number of iterations need to be executed to understand interesting biological phenomenon. The Blue Gene/L machine is a massive source of compute power. It consists of tens of thousands of embedded Power PC 440 processors. In this paper, we present several techniques to scale NAMD to 8192 processors of Blue Gene/L. These include topology specific optimizations, new messaging protocols, load-balancing, and overlap of computation and communication. We were able to achieve 1.2 TF of peak performance for cutoff simulations and 0.99 TF with PME.