With the ever-growing need of data in HPC applications, the congestion at the I O level becomes critical in super-computers. Architectural enhancement such as burst-buffers and pre-fetching are added to machines, but are not sufficient to prevent congestion. Recent online I O scheduling strategies have been put in place, but they add an additional congestion point and overheads in the computation of applications. In this work, we show how to take advantage of the periodic nature of HPC applications in order to develop efficient periodic scheduling strategies for their I O transfers. Our strategy computes once during the job scheduling phase a pattern where it defines the I O behavior for each application, after which the applications run independently, transferring their I O at the specified times. Our strategy limits the amount of I O congestion at the I O node level and can be easily integrated into current job schedulers. We validate this model through extensive simulations and experiments by comparing it to state-of-the-art online solutions, showing that not only our scheduler has the advantage of being de-centralized and thus overcoming the overhead of online schedulers, but also that it performs better than these solutions, improving the application dilation up to 13 and the maximum system efficiency up to 18 .
The study from @cite_8 offers ways of isolating the performance experienced by applications of one operating system from variations in the I O request stream characteristics of applications of other operating systems. While their solution cannot be applied to HPC systems, the study offers a way of controlling the coarse grain allocation of disk time to the different operating system instances as well as determining the fine-grain interleaving of requests from the corresponding operating systems to the storage system.
@cite_8
2018997957
Virtualized storage systems are required to service concurrently executing workloads, with potentially diverse data delivery requirements, that are running under multiple operating systems. Although a number of algorithms have been developed for I O performance virtualization among operating system (OS) instances and their applications, none results in absolute performance virtualization. By absolute performance virtualization we mean that the performance experienced by applications of one operating system does not suffer due to variations in the I O request stream characteristics of applications of other operating systems. Key requirements of I O performance virtualization are fairness and performance isolation. In this paper, we present a novel virtual I O scheduler (VIOS) that provides absolute performance virtualization by being fair in sharing I O system resources among operating systems and their applications, and provides performance isolation in the face of variations in the characteristics of I O streams. The VIOS controls the coarse grain allocation of disk time to the different operating system instances and is OS independent; optionally, a set of OS-dependent schedulers may determine the fine-grain interleaving of requests from the corresponding operating systems to the storage system. We consider the problem of how to provide an execution environment where the application's secrets are safe even in the presence of malicious system software layers. We propose Iso-X --- a flexible, fine-grained hardware-supported framework that provides isolation for security-critical pieces of an application such that they can execute securely even in the presence of untrusted system software. Isolation in Iso-X is achieved by creating and dynamically managing compartments to host critical fragments of code and associated data. Iso-X provides fine-grained isolation at the memory-page level, flexible allocation of memory, and a low-complexity, hardware-only trusted computing base. Iso-X requires minimal additional hardware, a small number of new ISA instructions to manage compartments, and minimal changes to the operating system which need not be in the trusted computing base. The run-time performance overhead of Iso-X is negligible and even the overhead of creating and destroying compartments is modest. Iso-X offers higher memory flexibility than the recently proposed SGX design from Intel, allowing both fluid partitioning of the vailable memory space and dynamic growth of compartments. An FPGA implementation of Iso-X runtime mechanisms shows a negligible impact on the processor cycle time. Commodity computer systems today do not include a full trusted path capability. Consequently, malware can control the user's input and output in order to reveal sensitive information to malicious parties or to generate manipulated transaction requests to service providers. Recent hardware offers compelling features for remote attestation and isolated code execution, however, these mechanisms are not widely used in deployed systems to date. We show how to leverage these mechanisms to establish a “one-way” trusted path allowing service providers to gain assurance that users' transactions were indeed submitted by a human operating the computer, instead of by malware such as transaction generators. We design, implement, and evaluate our solution, and argue that it is practical and offers immediate value in e-commerce, as a replacement for captchas, and in other Internet scenarios. MEMS-based storage devices promise significant performance, reliability, and power improvements relative to disk drives. This paper compares and contrasts these two storage technologies and explores how the physical characteristics of MEMS-based storage devices change four aspects of operating system (OS) management: request scheduling, data placement, failure management, and power conservation. Straightforward adaptations of existing disk request scheduling algorithms are found to be appropriate for MEMS-based storage devices. A new bipartite data placement scheme is shown to better match these devices' novel mechanical positioning characteristics. With aggressive internal redundancy, MEMS-based storage devices can mask and tolerate failure modes that halt operation or cause data loss for disks. In addition, MEMS-based storage devices simplify power management because the devices can be stopped and started rapidly.