Design Space Exploration and Resource Management of Multi/Many-Core Systems

The increasing demand of processing a higher number of applications and related data on computing platforms has resulted in reliance on multi-/many-core chips as they facilitate parallel processing. However, there is a desire for these platforms to be energy-efficient and reliable, and they need to perform secure computations for the interest of the whole community. This book provides perspectives on the aforementioned aspects from leading researchers in terms of state-of-the-art contributions and upcoming trends

Hyperscale Data Processing With Network-Centric Designs

Today’s largest data processing workloads are hosted in cloud data centers. Due to unprecedented data growth and the end of Moore’s Law, these workloads have ballooned to the hyperscale level, encompassing billions to trillions of data items and hundreds to thousands of machines per query. Enabling and expanding with these workloads are highly scalable data center networks that connect up to hundreds of thousands of networked servers. These massive scales fundamentally challenge the designs of both data processing systems and data center networks, and the classic layered designs are no longer sustainable. Rather than optimize these massive layers in silos, we build systems across them with principled network-centric designs. In current networks, we redesign data processing systems with network-awareness to minimize the cost of moving data in the network. In future networks, we propose new interfaces and services that the cloud infrastructure offers to applications and codesign data processing systems to achieve optimal query processing performance. To transform the network to future designs, we facilitate network innovation at scale. This dissertation presents a line of systems work that covers all three directions. It first discusses GraphRex, a network-aware system that combines classic database and systems techniques to push the performance of massive graph queries in current data centers. It then introduces data processing in disaggregated data centers, a promising new cloud proposal. It details TELEPORT, a compute pushdown feature that eliminates data processing performance bottlenecks in disaggregated data centers, and Redy, which provides high-performance caches using remote disaggregated memory. Finally, it presents MimicNet, a fine-grained simulation framework that evaluates network proposals at datacenter scale with machine learning approximation. These systems demonstrate that our ideas in network-centric designs achieve orders of magnitude higher efficiency compared to the state of the art at hyperscale

Space and Earth Sciences, Computer Systems, and Scientific Data Analysis Support, Volume 1

This Final Progress Report covers the specific technical activities of Hughes STX Corporation for the last contract triannual period of 1 June through 30 Sep. 1993, in support of assigned task activities at Goddard Space Flight Center (GSFC). It also provides a brief summary of work throughout the contract period of performance on each active task. Technical activity is presented in Volume 1, while financial and level-of-effort data is presented in Volume 2. Technical support was provided to all Division and Laboratories of Goddard's Space Sciences and Earth Sciences Directorates. Types of support include: scientific programming, systems programming, computer management, mission planning, scientific investigation, data analysis, data processing, data base creation and maintenance, instrumentation development, and management services. Mission and instruments supported include: ROSAT, Astro-D, BBXRT, XTE, AXAF, GRO, COBE, WIND, UIT, SMM, STIS, HEIDI, DE, URAP, CRRES, Voyagers, ISEE, San Marco, LAGEOS, TOPEX/Poseidon, Pioneer-Venus, Galileo, Cassini, Nimbus-7/TOMS, Meteor-3/TOMS, FIFE, BOREAS, TRMM, AVHRR, and Landsat. Accomplishments include: development of computing programs for mission science and data analysis, supercomputer applications support, computer network support, computational upgrades for data archival and analysis centers, end-to-end management for mission data flow, scientific modeling and results in the fields of space and Earth physics, planning and design of GSFC VO DAAC and VO IMS, fabrication, assembly, and testing of mission instrumentation, and design of mission operations center