Toward a Core Design to Distribute an Execution on a Many-Core Processor

International audienceThis paper presents a parallel execution model and a many-core processor design to run C programs in parallel. The model automatically builds parallel sections of machine instructions from the run trace. It parallelizes instructions fetches, renamings, executions and retirements. Predictor based fetch is replaced by a fetch-decode-and-partly-execute stage able to compute in-order most of the control instructions. Tomasulo's register renaming is extended to memory with a technique to match consumer/producer pairs. The Reorder Buffer is adapted to allow parallel retirement. The model is presented on a sum reduction example which is also used to give a short analytical evaluation of the model performance potential

ParaDIME: Parallel Distributed Infrastructure for Minimization of Energy for data centers

Dramatic environmental and economic impact of the ever increasing power and energy consumption of modern computing devices in data centers is now a critical challenge. On the one hand, designers use technology scaling as one of the methods to face the phenomenon called dark silicon (only segments of a chip function concurrently due to power restrictions). On the other hand, designers use extreme-scale systems such as teradevices to meet the performance needs of their applications which in turn increases the power consumption of the platform. In order to overcome these challenges, we need novel computing paradigms that address energy efficiency. One of the promising solutions is to incorporate parallel distributed methodologies at different abstraction levels. The FP7 project ParaDIME focuses on this objective to provide different distributed methodologies (software-hardware techniques) at different abstraction levels to attack the power-wall problem. In particular, the ParaDIME framework will utilize: circuit and architecture operation below safe voltage limits for drastic energy savings, specialized energy-aware computing accelerators, heterogeneous computing, energy-aware runtime, approximate computing and power-aware message passing. The major outcome of the project will be a noval processor architecture for a heterogeneous distributed system that utilizes future device characteristics, runtime and programming model for drastic energy savings of data centers. Wherever possible, ParaDIME will adopt multidisciplinary techniques, such as hardware support for message passing, runtime energy optimization utilizing new hardware energy performance counters, use of accelerators for error recovery from sub-safe voltage operation, and approximate computing through annotated code. Furthermore, we will establish and investigate the theoretical limits of energy savings at the device, circuit, architecture, runtime and programming model levels of the computing stack, as well as quantify the actual energy savings achieved by the ParaDIME approach for the complete computing stack with the real environment

A Role for Fucose α(1−2) Galactose Carbohydrates in Neuronal Growth

We report a fucose α(1−2) galactose-mediated pathway for the modulation of neuronal growth and morphology. Our studies provide strong evidence for the presence of Fucα(1−2)Gal glycoproteins and lectin receptors in hippocampal neurons. Additionally, we show that manipulation of Fucα(1−2)Gal-associated proteins using small-molecule and lectin probes induces dramatic changes in neuronal morphology. These findings may provide a novel pathway to stimulate neuronal growth and regeneration

Direct instruction wakeup for out-of-order processors

Instruction queues consume a significant amount of power in high-performance processors, primarily due to instruction wakeup logic access to the queue structures. The wakeup logic delay is also a critical timing parameter. This paper proposes a new queue organization using a small number of successor pointers plus a small number of dynamically allocated full successor bit vectors for cases with a larger number of successors. The details of the new organization are described and it is shown to achieve the performance of CAM-based or full dependency matrix organizations using just one pointer per instruction plus eight full bit vectors. Only two full bit vectors are needed when two successor pointers are stored per instruction. Finally, a design and pre-layout of all critical structures in 70 nm technology was performed for the proposed organization as well as for a CAM-based baseline. The new design is shown to use 1/2 to 1/5th of the baseline instruction queue power, depending on queue size. It is also shown to use significantly less power than the full dependency matrix based design.Peer ReviewedPostprint (published version

The Portrayal of Complementary and Alternative Medicine in Mass Print Magazines Since 1980

Objectives: The objectives of this study were to examine and describe the portrayal of complementary and alternative medicine (CAM) in mass print media magazines. Design: The sample included all 37 articles found in magazines with circulation rates of greater than 1 million published in the United States and Canada from 1980 to 2005. The analysis was quantitative and qualitative and included investigation of both manifest and latent magazine story messages. Results: Manifest analysis noted that CAM was largely represented as a treatment for a patient with a medically diagnosed illness or specific symptoms. Discussions used biomedical terms such as patient rather than consumer and disease rather than wellness. Latent analysis revealed three themes: (1) CAMs were described as good but not good enough; (2) individualism and consumerism were venerated; and (3) questions of costs were raised in the context of confusion and ambivalence

Implications of non-volatile memory as primary storage for database management systems

Traditional Database Management System (DBMS) software relies on hard disks for storing relational data. Hard disks are cheap, persistent, and offer huge storage capacities. However, data retrieval latency for hard disks is extremely high. To hide this latency, DRAM is used as an intermediate storage. DRAM is significantly faster than disk, but deployed in smaller capacities due to cost and power constraints, and without the necessary persistency feature that disks have. Non-Volatile Memory (NVM) is an emerging storage class technology which promises the best of both worlds. It can offer large storage capacities, due to better scaling and cost metrics than DRAM, and is non-volatile (persistent) like hard disks. At the same time, its data retrieval time is much lower than that of hard disks and it is also byte-addressable like DRAM. In this paper, we explore the implications of employing NVM as primary storage for DBMS. In other words, we investigate the modifications necessary to be applied on a traditional relational DBMS to take advantage of NVM features. As a case study, we have modified the storage engine (SE) of PostgreSQL enabling efficient use of NVM hardware. We detail the necessary changes and challenges such modifications entail and evaluate them using a comprehensive emulation platform. Results indicate that our modified SE reduces query execution time by up to 40% and 14.4% when compared to disk and NVM storage, with average reductions of 20.5% and 4.5%, respectively. © 2016 IEEE

Sulfation patterns of glycosaminoglycans encode molecular recognition and activity

Although glycosaminoglycans contribute to diverse physiological processes, an understanding of their molecular mechanisms has been hampered by the inability to access homogeneous glycosaminoglycan structures. Here, we assembled well-defined chondroitin sulfate oligosaccharides using a convergent, synthetic approach that permits installation of sulfate groups at precise positions along the carbohydrate backbone. Using these defined structures, we demonstrate that specific sulfation motifs function as molecular recognition elements for growth factors and modulate neuronal growth. These results provide both fundamental insights into the role of sulfation and direct evidence for a 'sulfation code' whereby glycosaminoglycans encode functional information in a sequence-specific manner analogous to that of DNA, RNA and proteins