Charles O. Schulz

Durable memory RS/6000 system design

The DM/6000 prototype is a fault-tolerant/durable-memory RS/6000. The main storage of this system is battery backed so as to maintain memory content across prolonged power interruptions. In addition, there are no single points of failure, and all likely multiple failure scenarios are covered. The prototype is intended to match the data integrity and availability characteristics of RAID5 disks. Redundancy is managed in hardware and in transparent to the software; application programs and the operating system (AIX) can run unmodified. The prototype is based on the IBM PowerPC 601 microprocessor operating at 80 MHz and is equivalent in performance and software appearance to a conventional 4-way shared bus, cache coherent, symmetric multiprocessor (SMP), with 4 gigabytes of non-volatile main storage.<<ETX>>

Using virtualization for high availability and disaster recovery

Traditional high-availability and disaster recovery solutions require proprietary hardware, complex configurations, applicationspecific logic, highly skilled personnel, and a rigorous and lengthy testing process. The resulting high costs have limited their adoption to environments with the most critical applications. However, high availability and disaster recovery are becoming increasingly important in many environments that cannot bear the complexity and the expense involved. In this paper, we show that virtualization can be used to develop solutions that meet this market demand. We describe the recently released Virtual Availability Manager (VAM) product offering, which provides simplified availability solutions using Xent-based virtualization, and which is available as part of the IBM Systems Director product. We present key design principles of VAM, explain its architecture and current capabilities, and describe the way it is being extended to enable recovery in case of disaster.

Virtual Hypervisor: Enabling fair and economical resource partitioning in cloud environments

Virtualization has rapidly gained popularity affecting multiple levels of computing stack. Since it decouples resources from their users it provides greater flexibility in terms of resource allocation but also brings new challenges for optimal design, provisioning and runtime management of systems. Cloud computing is a paradigm of computing that offers virtualized resources “as a service.” Cloud Managers are responsible for lifecycle management of virtual resources, efficient utilization of physical resources and exposing basic operational APIs to users. Software solutions can then be deployed on these virtual resources. In this paper we propose a Virtual Hypervisor abstraction allowing solution managers to have an improved control over the resource allocation decisions regarding their virtual machines while maintaining cloud managers role as the ultimate physical resource manager. We also introduce a novel resource allocation algorithm illustrating how the Virtual Hypervisor abstraction can be efficiently realized by the global cloud manager. We also use simulations to illustrate that our algorithm can be used to achieve fairer resource sharing and isolation across different Virtual Hypervisors.

Reliability-availability-serviceability characteristics of a compressed-memory system

New compression innovations and high-density silicon technology enable us to introduce main-memory compression. This technology is able to achieve, in most cases, 2:1 or better compression without impacting performance. It provides an enormous cost/performance advantage, given the cost content of memory in modern enterprise servers. The complex and highly parallel data manipulations central to this compression implementation would, if unprotected by extensive error detection and error correction techniques, offer several potential data integrity exposures. This paper describes the memory subsystem of an enterprise class server with a compressed mainstore and the methods which have been employed to guarantee the integrity of the compressed data. These methods consist of a novel ECC algorithm which includes address information in the code words, the use of CRC codes for compressed data blocks, and various consistency checks on the memory management structures used in the management of a compressed mainstore.

Scalable Metering for an Affordable IT Cloud Service Management

As the cloud services journey through their life-cycle towards commodities, cloud service providers have to carefully choose the metering and rating tools and scale their infrastructure to effectively process the collected metering data. In this paper, we focus on the metering and rating aspects of the revenue management and their adaptability to business and operational changes. We design a framework for IT cloud service providers to scale their revenue systems in a cost-aware manner. The main idea is to dynamically use existing or newly provisioned SaaS VMs, instead of dedicated setups, for deploying the revenue management systems. At on-boarding of new customers, our framework performs off-line analysis to recommend appropriate revenue tools and their scalable distribution by predicting the need for resources based on historical usage. This allows the revenue management to adapt to the ever evolving business context. We evaluated our framework on a test bed of 20 physical machines that were used to deploy 12 VMs within Open Stack environment. Our analysis shows that service management related tasks can be offloaded to the existing VMs with at most 15% overhead in CPU utilization, 10% overhead for memory usage, and negligible overhead for I/O and network usage. By dynamically scaling the setup, we were able to reduce the metering data processing time by many folds without incurring any additional cost.

Leveraging cloud in the rapidly evolving workplace of the future

Rapid advances in cloud computing have made it possible to replace individual working environments with centralized and consolidated workplaces. These workplaces bring many advantages over traditional self-managed environments, such as improved security and compliance, and rapid on-boarding. In this paper we describe the implementation of a desktop cloud at IBM Research.