Kyung Dong Ryu

Dynamic and adaptive updates of non-quiescent subsystems in commodity operating system kernels

Continuously running systems require kernel software updates applied to them without downtime. Facilitating fast reboots, or delaying an update may not be a suitable solution in many environments, especially in pay-per-use high-performance computing clusters and mission critical systems. Such systems will not reap the benefits of new kernel features, and will continue to operate with kernel security holes unpatched, at least until the next scheduled maintenance downtime. To address these problems we developed an on-the-fly kernel updating system that enables commodity operating systems to gain adaptive and mutative capabilities without kernel recompilation or reboot. Our system, DynAMOS, employs a novel and efficient dynamic code instrumentation technique termed adaptive function cloning. Execution flow can be switched adaptively among multiple editions of functions, possibly concurrently running. This approach becomes the foundation for dynamic replacement of non-quiescent kernel subsystems when the timeliness of an update depends on synchronization of multiple kernel paths. We illustrate our experience by dynamically updating core subsystems of the Linux kernel.

Structuring Peer-to-Peer Networks Using Interest-Based Communities

Interest-based communities are a natural arrangement of distributed systems that prune the search space and allow for better dissemination of information to participating peers. In this paper, we introduce the notion of peer communities. Communities are like interest groups, modeled after human communities and can overlap. Our work focuses on providing efficient formation, discovery and management techniques that can be implemented to constantly changing community structures. We provide a mechanism to generate realistic peer-to-peer network topologies that can be used in simulations that evaluate the operation of our algorithms. Our experiments show how searching the peer-to-peer network can take advantage of peer communities to reduce the number of messages and improve the quality of search results.

Active Memory Cube: A processing-in-memory architecture for exascale systems

Many studies point to the difficulty of scaling existing computer architectures to meet the needs of an exascale system (i.e., capable of executing

An efficient peer-to-peer file sharing exploiting hierarchy and asymmetry

10^{18}

Applications Know Best: Performance-Driven Memory Overcommit with Ginkgo

floating-point operations per second), consuming no more than 20 MW in power, by around the year 2020. This paper outlines a new architecture, the Active Memory Cube, which reduces the energy of computation significantly by performing computation in the memory module, rather than moving data through large memory hierarchies to the processor core. The architecture leverages a commercially demonstrated 3D memory stack called the Hybrid Memory Cube, placing sophisticated computational elements on the logic layer below its stack of dynamic random-access memory (DRAM) dies. The paper also describes an Active Memory Cube tuned to the requirements of a scientific exascale system. The computational elements have a vector architecture and are capable of performing a comprehensive set of floating-point and integer instructions, predicated operations, and gather-scatter accesses across memory in the Cube. The paper outlines the software infrastructure used to develop applications and to evaluate the architecture, and describes results of experiments on application kernels, along with performance and power projections.

CloudBench: Experiment Automation for Cloud Environments

Many peer-to-peer (P2P) file sharing systems have been proposed to take advantage of high scalability and abundant resources at end-user machines. Previous approaches adopted either simple flooding or routing with complex structures, such as distributed hashing tables (DHT). However, these approaches did not consider the heterogeneous nature of the machines and the hierarchy of networks on the Internet. This paper presents the peer-to-peer asymmetric file sharing system (PASS), a novel approach to P2P file sharing, which accounts for the different capabilities and network locations of the participating machines. Our system selects only a portion of high-capacity machines (supernodes) for routing support, and organizes the network by using location information. We show that our key-coverage based directory replication improves the file search performance to a small constant number of routing hops, regardless of the network size.

A role-based trust model for peer-to-peer communities and dynamic coalitions

Memory over commitment enables cloud providers to host more virtual machines on a single physical server, exploiting spare CPU and I/O capacity when physical memory becomes the bottleneck for virtual machine deployment. However, over commiting memory can also cause noticeable application performance degradation. We present Ginkgo, a policy framework for over omitting memory in an informed and automated fashion. By directly correlating application-level performance to memory, Ginkgo automates the redistribution of scarce memory across all virtual machines, satisfying performance and capacity constraints. Ginkgo also achieves memory gains for traditionally fixed-size Java applications by coordinating the redistribution of available memory with the activities of the Java Virtual Machine heap. When compared to a non-over commited system, Ginkgo runs the Day Trader 2.0 and SPEC Web 2009 benchmarks with the same number of virtual machines while saving up to 73% (50% omitting free space) of a physical servers memory while keeping application performance degradation within 7%.

FusedOS: Fusing LWK Performance with FWK Functionality in a Heterogeneous Environment

The growth in the adoption of cloud computing is driven by distinct and clear benefits for both cloud customers and cloud providers. However, the increase in the number of cloud providers as well as in the variety of offerings from each provider has made it harder for customers to choose. At the same time, the number of options to build a cloud infrastructure, from cloud management platforms to different interconnection and storage technologies, also poses a challenge for cloud providers. In this context, cloud experiments are as necessary as they are labor intensive. Cloud Bench [1] is an open-source framework that automates cloud-scale evaluation and benchmarking through the running of controlled experiments, where complex applications are automatically deployed. Experiments are described through experiment plans, containing directives with enough descriptive power to make the experiment descriptions brief while allowing for customizable multi-parameter variation. Experiments can be executed in multiple clouds using a single interface. Cloud Bench is capable of managing experiments spread across multiple regions and for long periods of time. The modular approach adopted allows it to be easily extended to accommodate new cloud infrastructure APIs and benchmark applications, directly by external users. A built-in data collection system collects, aggregates and stores metrics for cloud management activities (such as VM provisioning and VM image capture) and application runtime information. Experiments can be conducted in a highly controllable fashion, in order to assess the stability, scalability and reliability of multiple cloud configurations. We demonstrate Cloud Benchs main characteristics through the evaluation of an Open Stack installation, including experiments with approximately 1200 simultaneous VMs at an arrival rate of up to 400 VMs/hour.

On fault resilience of OpenStack

Although P2P systems are usually used for information exchange between peers, they have either protected peers anonymity, or required transacting peers to trust each other implicitly. Both these approaches are vulnerable to attacks by malicious peers who could abuse the P2P system to spread viruses, incorrect, or damaging information. Here, we propose an approach for trust management in P2P systems. We introduce an optimistic role-based model for trust amongst peers and show that it is scalable, dynamic, revocable, secure and transitive. Our proposed solution permits asymmetric trust relationships that can be verified by any peer in the system through a simple, low-cost algorithm. We introduce a metric known as iComplex that combines a peers trust value for each of its roles into a single, relative, probabilistic guarantee of trust. Finally, we discuss how our trust model allows peers to revoke relationships with malicious peers, and the nonrepudiation of peer relations. We use simulations to illustrate the trust value distribution amongst peers in the network. Our analysis and experiments demonstrates the low-cost involved to verify and validate trust values. Lastly, we establish the effectiveness of using sum as the aggregation function to combine trust values of a peer.

Conditional Memory Ordering

Traditionally, there have been two approaches to providing an operating environment for high performance computing (HPC). A Full-Weight Kernel(FWK) approach starts with a general-purpose operating system and strips it down to better scale up across more cores and out across larger clusters. A Light-Weight Kernel (LWK) approach starts with a new thin kernel code base and extends its functionality by adding more system services needed by applications. In both cases, the goal is to provide end-users with a scalable HPC operating environment with the functionality and services needed to reliably run their applications. To achieve this goal, we propose a new approach, called Fused OS, that combines the FWK and LWK approaches. Fused OS provides an infrastructure capable of partitioning the resources of a multicoreheterogeneous system and collaboratively running different operating environments on subsets of the cores and memory, without the use of a virtual machine monitor. With Fused OS, HPC applications can enjoy both the performance characteristics of an LWK and the rich functionality of an FWK through cross-core system service delegation. This paper presents the Fused OS architecture and a prototype implementation on Blue Gene/Q. The Fused OS prototype leverages Linux with small modifications as a FWK and implements a user-level LWK called Compute Library (CL) by leveraging CNK. We present CL performance results demonstrating low noise and show micro-benchmarks running with performance commensurate with that provided by CNK.