ترغب بنشر مسار تعليمي؟ اضغط هنا

Espresso: Brewing Java For More Non-Volatility with Non-volatile Memory

79   0   0.0 ( 0 )
 نشر من قبل Mingyu Wu
 تاريخ النشر 2017
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

Fast, byte-addressable non-volatile memory (NVM) embraces both near-DRAM latency and disk-like persistence, which has generated considerable interests to revolutionize system software stack and programming models. However, it is less understood how NVM can be combined with managed runtime like Java virtual machine (JVM) to ease persistence management. This paper proposes Espresso, a holistic extension to Java and its runtime, to enable Java programmers to exploit NVM for persistence management with high performance. Espresso first provides a general persistent heap design called Persistent Java Heap (PJH) to manage persistent data as normal Java objects. The heap is then strengthened with a recoverable mechanism to provide crash consistency for heap metadata. It then provides a new abstraction called Persistent Java Object (PJO) to provide an easy-to-use but safe persistent programming model for programmers to persist application data. The evaluation confirms that Espresso significantly outperforms state-of-art NVM support for Java (i.e., JPA and PCJ) while being compatible to existing data structures in Java programs.

قيم البحث

اقرأ أيضاً

We introduce a fully automated static analysis that takes a sequential Java bytecode program P as input and attempts to prove that there exists an infinite execution of P. The technique consists in compiling P into a constraint logic program P_CLP an d in proving non-termination of P_CLP; when P consists of instructions that are exactly compiled into constraints, the non-termination of P_CLP entails that of P. Our approach can handle method calls; to the best of our knowledge, it is the first static approach for Java bytecode able to prove the existence of infinite recursions. We have implemented our technique inside the Julia analyser. We have compared the results of Julia on a set of 113 programs with those provided by AProVE and Invel, the only freely usable non-termination analysers comparable to ours that we are aware of. Only Julia could detect non-termination due to infinite recursion.
We present the first demonstration of an integrated photonic phase-change memory using GeSbTe-225 on silicon-on-insulator and demonstrate reliable multilevel operation with a single programming pulse. We also compare our results on silicon with previ ous demonstrations on silicon nitride. Crucially, achieving this on silicon enables tighter integration of traditional electronics with photonic memories in future, making phase-change photonic memory a viable and integrable technology.
DNA sequencing is the physical/biochemical process of identifying the location of the four bases (Adenine, Guanine, Cytosine, Thymine) in a DNA strand. As semiconductor technology revolutionized computing, modern DNA sequencing technology (termed Nex t Generation Sequencing, NGS)revolutionized genomic research. As a result, modern NGS platforms can sequence hundreds of millions of short DNA fragments in parallel. The sequenced DNA fragments, representing the output of NGS platforms, are termed reads. Besides genomic variations, NGS imperfections induce noise in reads. Mapping each read to (the most similar portion of) a reference genome of the same species, i.e., read mapping, is a common critical first step in a diverse set of emerging bioinformatics applications. Mapping represents a search-heavy memory-intensive similarity matching problem, therefore, can greatly benefit from near-memory processing. Intuition suggests using fast associative search enabled by Ternary Content Addressable Memory (TCAM) by construction. However, the excessive energy consumption and lack of support for similarity matching (under NGS and genomic variation induced noise) renders direct application of TCAM infeasible, irrespective of volatility, where only non-volatile TCAM can accommodate the large memory footprint in an area-efficient way. This paper introduces GeNVoM, a scalable, energy-efficient and high-throughput solution. Instead of optimizing an algorithm developed for general-purpose computers or GPUs, GeNVoM rethinks the algorithm and non-volatile TCAM-based accelerator design together from the ground up. Thereby GeNVoM can improve the throughput by up to 113.5 times (3.6); the energy consumption, by up to 210.9 times (1.36), when compared to a GPU (accelerator) baseline, which represents one of the highest-throughput implementations known.
Information technologies require entangling data stability with encryption for a next generation of secure data storage. Current magnetic memories, ranging from low-density stripes up to high-density hard drives, can ultimately be detected using rout inely available probes or manipulated by external magnetic perturbations. Antiferromagnetic resistors feature unrivalled robustness but the stable resistive states reported scarcely differ by more than a fraction of a percent at room temperature. Here we show that the metamagnetic (ferromagnetic to antiferromagnetic) transition in intermetallic Fe0.50Rh0.50 can be electrically controlled in a magnetoelectric heterostructure to reveal or cloak a given ferromagnetic state. From an aligned ferromagnetic phase, magnetic states are frozen into the antiferromagnetic phase by the application of an electric field, thus eliminating the stray field and likewise making it insensitive to external magnetic field. Application of a reverse electric field reverts the antiferromagnetic state to the original ferromagnetic state. Our work demonstrates the building blocks of a feasible, extremely stable, non-volatile, electrically addressable, low-energy dissipation, magnetoelectric multiferroic memory.
We firstly suggest new cache policy applying the duty to delete invalid cache data on Non-volatile Memory (NVM). This cache policy includes generating random data and overwriting the random data into invalid cache data. Proposed cache policy is more economical and effective regarding perfect deletion of data. It is ensure that the invalid cache data in NVM is secure against malicious hackers.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا