Linux kernel compaction through cold code swapping

There is a growing trend to use general-purpose operating systems like Linux in embedded systems. Previous research focused on using compaction and specialization techniques to adapt a general-purpose OS to the memory-constrained environment, presented by most, embedded systems. However, there is still room for improvement: it has been shown that even after application of the aforementioned techniques more than 50% of the kernel code remains unexecuted under normal system operation. We introduce a new technique that reduces the Linux kernel code memory footprint, through on-demand code loading of infrequently executed code, for systems that support virtual memory. In this paper, we describe our general approach, and we study code placement algorithms to minimize the performance impact of the code loading. A code, size reduction of 68% is achieved, with a 2.2% execution speedup of the system-mode execution time, for a case study based on the MediaBench II benchmark suite

Reductie van het geheugengebruik van besturingssysteemkernen Memory Footprint Reduction for Operating System Kernels

In ingebedde systemen is er vaak maar een beperkte hoeveelheid geheugen beschikbaar. Daarom wordt er veel aandacht besteed aan het produceren van compacte programma's voor deze systemen, en zijn er allerhande technieken ontwikkeld die automatisch het geheugengebruik van programma's kunnen verkleinen. Tot nu toe richtten die technieken zich voornamelijk op de toepassingssoftware die op het systeem draait, en werd het besturingssysteem over het hoofd gezien. In dit proefschrift worden een aantal technieken beschreven die het mogelijk maken om op een geautomatiseerde manier het geheugengebruik van een besturingssysteemkern gevoelig te verkleinen. Daarbij wordt in eerste instantie gebruik gemaakt van compactietransformaties tijdens het linken. Als we de hardware en software waaruit het systeem samengesteld is kennen, is het mogelijk om nog verdere reducties te bekomen. Daartoe wordt de kern gespecialiseerd voor een bepaalde hardware-software combinatie. Overbodige functionaliteit wordt opgespoord en uit de kern verwijderd, terwijl de resterende functionaliteit wordt aangepast aan de specifieke gebruikspatronen die uit de hardware en software kunnen afgeleid worden. Als laatste worden technieken voorgesteld die het mogelijk maken om weinig of niet uitgevoerde code (bijvoorbeeld code voor het afhandelen van slechts zeldzaam optredende foutcondities) uit het geheugen te verwijderen. Deze code wordt dan enkel ingeladen op het moment dat ze effectief nodig is. Voor ons testsysteem kunnen we met de gecombineerde technieken het geheugengebruik van een Linux 2.4 kern met meer dan 48% verminderen

Verification of the Tree-Based Hierarchical Read-Copy Update in the Linux Kernel

Read-Copy Update (RCU) is a scalable, high-performance Linux-kernel synchronization mechanism that runs low-overhead readers concurrently with updaters. Production-quality RCU implementations for multi-core systems are decidedly non-trivial. Giving the ubiquity of Linux, a rare "million-year" bug can occur several times per day across the installed base. Stringent validation of RCU's complex behaviors is thus critically important. Exhaustive testing is infeasible due to the exponential number of possible executions, which suggests use of formal verification. Previous verification efforts on RCU either focus on simple implementations or use modeling languages, the latter requiring error-prone manual translation that must be repeated frequently due to regular changes in the Linux kernel's RCU implementation. In this paper, we first describe the implementation of Tree RCU in the Linux kernel. We then discuss how to construct a model directly from Tree RCU's source code in C, and use the CBMC model checker to verify its safety and liveness properties. To our best knowledge, this is the first verification of a significant part of RCU's source code, and is an important step towards integration of formal verification into the Linux kernel's regression test suite.Comment: This is a long version of a conference paper published in the 2018 Design, Automation and Test in Europe Conference (DATE

Reducing Memory Footprint for In-Memory Root Filesystem (TMPFS)

This disclosure relates to the field of high-performance computing (HPC) clusters and techniques cluster managers or system administrators can use to avoid expensive and complicated storage for compute resources. By making in-memory root filesystems more desirable to use, it is easier to reduce hardware complexity and cost in the system

Governing with Insights: Towards Profile-Driven Cache Management of Black-Box Applications

There exists a divide between the ever-increasing demand for high-performance embedded systems and the availability of practical methodologies to understand the interplay of complex data-intensive applications with hardware memory resources. On the one hand, traditional static analysis approaches are seldomly applicable to latest-generation multi-core platforms due to a lack of accurate micro-architectural models. On the other hand, measurement-based methods only provide coarse-grained information about the end-to-end execution of a given real-time application. In this paper, we describe a novel methodology, namely Black-Box Profiling (BBProf), to gather fine-grained insights on the usage of cache resources in applications of realistic complexity. The goal of our technique is to extract the relative importance of individual memory pages towards the overall temporal behavior of a target application. Importantly, BBProf does not require the semantics of the target application to be known - i.e., applications are treated as black-boxes - and it does not rely on any platform-specific hardware support. We provide an open-source full-system implementation and showcase how BBProf can be used to perform profile-driven cache management

RAS enhancements for RDMA communications

textEthernet as the communication medium in the enterprise data center has outlived all competing mediums and resisted the test of time with regards to speed and costs. The future is also poised for growth with 40 and 100Gps speeds just over horizon. The current state of the technology is being enhanced and extended with lossless features to allow for fabric convergence of Storage and Inter Process Communication (IPC) Networks. It is under this medium that an increase in the adoption of Remote Direct Memory Access (RDMA) over Ethernet using offloaded TCP/IP (iWARP) and Infiniband over Ethernet (RoCE) communication stacks to RDMA capable NIC adapter s (RNIC) is observed. RDMA enables direct application to application communication over the network resulting in numerous and significant benefits such as reduced CPU utilization, lower latency communications, increased energy efficiency, and reduced overall system requirements. However, with said benefits also comes increased software complexity in how RDMA interface users communicate. The RDMA communication semantics, which originate from the HPC domain, are heavily biased towards Low-Latency and High-Bandwidth communications rather than Reliability, Availability, and Serviceability (RAS). As adoption increases, and enterprise data centers begins to leverage RDMA over Ethernet, enhancements to the OS stack software architecture and design of the components involved is required to address these deficiencies. Operating system interfaces, device drivers, adapter hardware design, and embedded firmware features must be viewed from a high-availability and maintainability point of view. RAS enhancements for RDMA communications proposes the software architectural tradeoffs for enhancing the iWARP and RoCE RDMA implementations for communications in the enterprise data center, with new and traditional RAS features for existing communications stacks and devices. The architecture leverages software enhancements in traceability, availability, maintainability, serviceability, fault-isolation and resource management; such that in the advent of errors, the probability that the forensics data points to identify root cause are immediately and automatically available is increased.Electrical and Computer Engineerin