Quality of Service Driven Runtime Resource Allocation in Reconfigurable HPC Architectures

Heterogeneous System Architectures (HSA) are gaining importance in the High Performance Computing (HPC) domain due to increasing computational requirements coupled with energy consumption concerns, which conventional CPU architectures fail to effectively address. Systems based on Field Programmable Gate Array (FPGA) recently emerged as an effective alternative to Graphical Processing Units (GPUs) for demanding HPC applications, although they lack the abstractions available in conventional CPU-based systems. This work tackles the problem of runtime resource management of a system using FPGA-based co-processors to accelerate multi-programmed HPC workloads. We propose a novel resource manager able to dynamically vary the number of FPGAs allocated to each of the jobs running in a multi-accelerator system, with the goal of meeting a given Quality of Service metric for the running jobs measured in terms of deadline or throughput. We implement the proposed resource manager in a commercial HPC system, evaluating its behavior with representative workloads

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

A fault-injection methodology for the system-level dependability analysis of multiprocessor embedded systems

This paper presents a methodology for the system-level dependability analysis of multiprocessor embedded systems. The methodology is based on fault injection and features an error analysis approach offering to the designer the possibility to specify custom monitoring and classification actions at both application and architecture levels. In particular, a debug-like mechanism offers the possibility to interpret architectural raw data observed during the simulation at application level with a function call/return granularity, thus offering the possibility to analyze the propagation of the errors in the various functionalities of the executed application. A framework for automating the proposed methodology has been implemented within a state-of-the-art SystemC/TLM simulation platform for multiprocessor specifications provided with a fault injection engine. The effectiveness of the methodology has been demonstrated in two different case studies, showing how the proposed approach is able to produce an accurate dependability report highlighting the criticalities in both the architecture and the application of the system under design

Automated Resource-aware Floorplanning of Reconfigurable Areas in Partially-Reconfigurable FPGA Systems

The floorplanning activity is a key step in the design of systems on FPGAs, but the approaches available today rarely consider both the constraints imposed by the heterogeneous distribution of the resources in the devices and the reconfiguration capabilities. In fact, current-generation FPGAs present a complex architecture, but also offer more sophisticated reconfiguration features. The proposed floor- planner, based on an accurate model of the devices, takes into account all these elements and finds an optimal solution, suitable for reconfigurable designs

Can Dark Silicon Be Exploited to Prolong System Lifetime?

Besides stringent power and thermal constraints, a dark silicon chip is also subjected to various reliability threats. This article illustrates how the dark silicon can be exploited to improve the chip’s lifetime through efficient utilization of computational resources and power budget, while still performing in a similar way