Gokul B. Kandiraju

Modeling and simulating flash based solid-state disks for operating systems

Solid-State Disks (SSDs) made out of Flash devices have gained a lot of prominence in recent years due to their increasing performance and endurance. A number of mechanisms are being proposed to improve the performance and reliability of these devices from technological and operating system perspectives, to integrate them into personal computers and enterprise systems. Most of such proposals are being implemented and evaluated directly on top of these SSDs and require sophisticated framework and infrastructure for thorough performance evaluation. On the other hand, to our knowledge, very little has been done on modeling Flash devices and building efficient Flash simulators that can be used to simulate SSDs. Such models and simulators can give insights to make design decisions, save a lot of cumbersome work for setup and implementation, save hardware costs and allow researchers to focus on the real methods that are being proposed. This paper presents a linear model for NAND-based Flash devices based on the internal architecture of these devices. Parameters of the model are presented along with micro-benchmarks that can be used to extract these parameters. The model is validated on the STEC Zeus Flash SSD and extracted parameters are used to build a Flash simulator as a kernel extension in the AIX operating system. A key feature of the simulator is that it simulates I/O requests by maintaining minimal state information and is independent of the internal organization of a Flash SSD. The simulator is validated using commercial and raw-IO applications through experimentation on the simulator and real Flash disks.

Software defined infrastructures

A fundamental component of any large-scale computer system is infrastructure. Cloud computing has completely changed the way infrastructure is viewed, offering more simplicity, flexibility, and monetary benefits compared to a traditional view of infrastructure. At the core of this transformation is the notion of virtualization of infrastructure as a whole, with providers offering infrastructure-as-a-service (IaaS) to consumers. However, just offering IaaS alone is insufficient for software defined environments (SDEs). This paper examines infrastructure in the context of SDE and discusses what we believe are some of the fundamental characteristics required of such infrastructure--called software defined infrastructure (SDI)--and how it fits into the larger landscape of cloud computing environments and SDEs. Various components of SDI are discussed, including core intelligence, monitoring pieces, and management, in addition to a brief discussion on silos such as compute, network and storage. Consumer and provider points of view are also presented along with infrastructure-level service-level agreements (SLAs). Also presented are the design principles and high-level architectural design of the infrastructure intelligence controller, which constantly transforms infrastructure to honor consumer requirements (SLAs) amidst provider constraints (costs). We believe that the insights presented in this paper can be used for better design of SDE architectures and of data-center systems software in general.

Investigating hybrid SSD FTL schemes for Hadoop workloads

The Flash Translation Layer (FTL) is the core engine for Solid State Disks (SSD). It is responsible for managing the virtual to physical address mappings and emulating the functionality of a normal block-level device. SSD performance is highly dependent on the design of the FTL. For the last few years, several FTL schemes have been proposed. Hybrid FTL schemes have gained more popularity since they try to combine the benefits of both page-level mapping and block-level mapping schemes. Examples include BAST, FAST, LAST, etc. To provide high performance, FTL designers face several cross cutting issues: the right balance between coarse and fine grain address mapping, the asymmetric nature of reads and writes, the write amplification property of Flash memory, and the wear-out behavior of flash. The MapReduce paradigm has become a very popular paradigm for performing parallel and distributed computations on large data. Hadoop, an open-source implementation of MapReduce, has accelerated MapReduce adoption. Flash SSD is increasingly being used as a storage solution in Hadoop deployments for faster processing and better energy utilization. Little work has been done to understand the endurance implications of SSD on Hadoop-based workloads. In this paper, using a highly flexible and reconfigurable kernel-level simulation infrastructure, we investigate the internal characteristics of various hybrid FTL schemes using a representative set of Hadoop workloads. Our investigation brings out the wear-out behavior of SSD for Hadoop-based workloads including wear-leveling details, garbage collection, translation and block/page mappings, and advocates the need for dynamic tuning of FTL parameters for these workloads.

A flexible OS-based approach for characterizing solid-state disk endurance

The performance and power benefits of Flash memory have paved its adoption in mass storage devices in the form of Solid-State Disks (SSDs). Despite these benefits, Flash memorys limited write endurance remains a big impediment to its wide adoption in the enterprise server market. Existing research efforts have mostly focused on proposing various mechanisms and algorithms to improve SSDs performance and reliability. However, there is still a lack of flexible tools that allow characterizing SSD endurance (i.e., wear-out behavior) and investigating its impact on applications without affecting the lifetime of the real SSD device. To address this issue, SolidSim, a kernel-level simulator has been enhanced with capabilities to simulate state-of-the-art wear-leveling, garbage-collection and other advanced internal management techniques of an SSD. These extensions have further increased SolidSims flexibility to study both SSD performance and endurance characteristics. Our approach allows investigating these characteristics without requiring any changes to applications or gathering any workload traces. The paper presents insights into wear-out behavior including logical, physical and translation characteristics, and correlates them with application behavior and SSD life-times using a set of representative workloads.

INFLOW 2015: The Third Workshop on Interactions of NVM/FLash with Operating systems and Workloa: INFLOW '15 Message from the Chairs

We would like first and foremost to thank the authors who chose to submit their papers to INFLOW ’15, who are responsible for ensuring that this workshop continues to represent some of the most cutting-edge research in storage systems. We are also grateful to the program committee for their efforts, providing three to four high-quality reviews for each paper, and to ACM SIGOPS for their support of this workshop. Finally we would like to thank the attendees at INFLOW ’15, who attended despite the concurrent SOSP History Day.