Emulating and evaluating hybrid memory for managed languages on NUMA hardware

Non-volatile memory (NVM) has the potential to become a mainstream memory technology and challenge DRAM. Researchers evaluating the speed, endurance, and abstractions of hybrid memories with DRAM and NVM typically use simulation, making it easy to evaluate the impact of different hardware technologies and parameters. Simulation is, however, extremely slow, limiting the applications and datasets in the evaluation. Simulation also precludes critical workloads, especially those written in managed languages such as Java and C#. Good methodology embraces a variety of techniques for evaluating new ideas, expanding the experimental scope, and uncovering new insights. This paper introduces a platform to emulate hybrid memory for managed languages using commodity NUMA servers. Emulation complements simulation but offers richer software experimentation. We use a thread-local socket to emulate DRAM and a remote socket to emulate NVM. We use standard C library routines to allocate heap memory on the DRAM and NVM sockets for use with explicit memory management or garbage collection. We evaluate the emulator using various configurations of write-rationing garbage collectors that improve NVM lifetimes by limiting writes to NVM, using 15 applications and various datasets and workload configurations. We show emulation and simulation confirm each other's trends in terms of writes to NVM for different software configurations, increasing our confidence in predicting future system effects. Emulation brings novel insights, such as the non-linear effects of multi-programmed workloads on NVM writes, and that Java applications write significantly more than their C++ equivalents. We make our software infrastructure publicly available to advance the evaluation of novel memory management schemes on hybrid memories

Crystal gazer : profile-driven write-rationing garbage collection for hybrid memories

Non-volatile memories (NVM) offer greater capacity than DRAM but suffer from high latency and low write endurance. Hybrid memories combine DRAM and NVM to form scalable memory systems with the promise of high capacity, low energy consumption, and high endurance. Automatically managing hybrid NVM-DRAM memories to achieve their promise without changing user applications or their programming models remains an open question. This paper uses garbage collection in managed languages to exploit NVM capacity while preventing NVM wear out in hybrid memories with no changes to the programming model. We introduce profile-driven write-rationing garbage collection. Allocation sites that produce frequently written objects are predicted based on previous program executions. Objects are initially allocated in a DRAM nursery space. The collector copies surviving nursery objects from highly written sites to a mature DRAM space and read-mostly objects to a mature NVM space.Write-intensity prediction for 15 Java benchmarks accurately places objects in the correct space, eliminating expensive object monitoring from prior write-rationing garbage collectors. Furthermore, our technique exposes a Pareto tradeoff between DRAM usage and NVM lifetime, unlike prior work. Experimental results on NUMA hardware that emulates hybrid NVM-DRAM memory demonstrates that profile-driven write-rationing garbage collection reduces the number of writes to NVM compared to prior work to extend its lifetime, maximizes the use of NVM for its capacity, and achieves good performance

Coverage-Based Debloating for Java Bytecode

Software bloat is code that is packaged in an application but is actually not necessary to run the application. The presence of software bloat is an issue for security, for performance, and for maintenance. In this paper, we introduce a novel technique for debloating Java bytecode, which we call coverage-based debloating. We leverage a combination of state-of-the-art Java bytecode coverage tools to precisely capture what parts of a project and its dependencies are used at runtime. Then, we automatically remove the parts that are not covered to generate a debloated version of the compiled project. We successfully generate debloated versions of 220 open-source Java libraries, which are syntactically correct and preserve their original behavior according to the workload. Our results indicate that 68.3% of the libraries' bytecode and 20.5% of their total dependencies can be removed through coverage-based debloating. Meanwhile, we present the first experiment that assesses the utility of debloated libraries with respect to client applications that reuse them. We show that 80.9% of the clients with at least one test that uses the library successfully compile and pass their test suite when the original library is replaced by its debloated version

Cooperative cache scrubbing

Managing the limited resources of power and memory bandwidth while improving performance on multicore hardware is challeng-ing. In particular, more cores demand more memory bandwidth, and multi-threaded applications increasingly stress memory sys-tems, leading to more energy consumption. However, we demon-strate that not all memory traffic is necessary. For modern Java pro-grams, 10 to 60 % of DRAM writes are useless, because the data on these lines are dead- the program is guaranteed to never read them again. Furthermore, reading memory only to immediately zero ini-tialize it wastes bandwidth. We propose a software/hardware coop-erative solution: the memory manager communicates dead and zero lines with cache scrubbing instructions. We show how scrubbing instructions satisfy MESI cache coherence protocol invariants and demonstrate them in a Java Virtual Machine and multicore simula-tor. Scrubbing reduces average DRAM traffic by 59%, total DRAM energy by 14%, and dynamic DRAM energy by 57 % on a range of configurations. Cooperative software/hardware cache scrubbing reduces memory bandwidth and improves energy efficiency, two critical problems in modern systems

Write-rationing garbage collection for hybrid memories

Emerging Non-Volatile Memory (NVM) technologies offer high capacity and energy efficiency compared to DRAM, but suffer from limited write endurance and longer latencies. Prior work seeks the best of both technologies by combining DRAM and NVM in hybrid memories to attain low latency, high capacity, energy efficiency, and durability. Coarse-grained hardware and OS optimizations then spread writes out (wear-leveling) and place highly mutated pages in DRAM to extend NVM lifetimes. Unfortunately even with these coarse-grained methods, popular Java applications exact impractical NVM lifetimes of 4 years or less. This paper shows how to make hybrid memories practical, without changing the programming model, by enhancing garbage collection in managed language runtimes. We find object write behaviors offer two opportunities: (1) 70% of writes occur to newly allocated objects, and (2) 2% of objects capture 81% of writes to mature objects. We introduce writerationing garbage collectors that exploit these fine-grained behaviors. They extend NVM lifetimes by placing highly mutated objects in DRAM and read-mostly objects in NVM. We implement two such systems. (1) Kingsguard-nursery places new allocation in DRAM and survivors in NVM, reducing NVM writes by 5x versus NVM only with wear-leveling. (2) Kingsguard-writers (KG-W) places nursery objects in DRAM and survivors in a DRAM observer space. It monitors all mature object writes and moves unwritten mature objects from DRAM to NVM. Because most mature objects are unwritten, KG-W exploits NVM capacity while increasing NVM lifetimes by 11x. It reduces the energy-delay product by 32% over DRAM-only and 29% over NVM-only. This work opens up new avenues for making hybrid memories practical

Ohjelmistojen ajonaikainen paisuminen: Syyt, seuraukset sekä ratkaisut

Tämä työ käsittelee ajonaikaista paisumista. Työn tarkoituksena on tutkia mitkä seikat aiheuttavat ajonaikaista paisumista, mitkä ovat sen vaikutukset sekä tutkia joitakin ratkaisuja ajonaikaiseen paisumiseen. Se pyrkii esittelemään lukijalleen mitä tarkoitetaan ajonaikaisella paisumisella, kuinka vakavia ovat sen vaikutukset sekä miten paisumista voidaan välttää sekä poistaa. Ajonaikaista paisumista aiheuttavat monet tekijät nykyaikaisessa ohjelmistokehityksessä. Nopeat sekä ketterät kehityssuunnat ohjelmistokehityksessä, kuten koodin uudelleenkäyttö sekä suurien kirjastojen implementaatio, voivat aiheuttaa vakavaa ajonaikaista paisumista ohjelmistoissa. Tämä paisuminen voi aiheuttaa ohjelmiston epätehokkuutta sekä epävakautta. Nopeasta ja ketterästä kehityksestä ei olla luopumassa, mutta jonkinlaisia ratkaisuja olisi hyvä löytää. Tarjolla on kuitenkin monia tekniikoita, joita voidaan ottaa käyttöön ohjelmistokehityksen aikana, joilla voidaan ajonaikaista paisumista vähentää. Nämä tekniikat voivat olla hyvin ihmislähtöistä koulutusta, jota tarjotaan ohjelmistokehittäjille, jotta he olisivat tietoisia paisumisen ongelmista. Tekniikat voivat myös olla täysin automatisoituja apu-ohjelmistoja, jotka ilmoittavat kehittäjille, jos heidän ohjelmistossaan on paisumis-ongelma