We present GekkoFS, a temporary, highly-scalable burst buffer file system which has been specifically optimized for new access patterns of data-intensive High-Performance Computing (HPC) applications. The file system provides relaxed POSIX semantics, only offering features which are actually required by most (not all) applications. It is able to provide scalable I/O performance and reaches millions of metadata operations already for a small number of nodes, significantly outperforming the capabilities of general-purpose parallel file systems.

Storage backends of parallel compute clusters are still based mostly on magnetic disks, while newer and faster storage technologies such as flash-based SSDs or non-volatile random access memory (NVRAM) are deployed within compute nodes. Including these new storage technologies into scientific workflows is unfortunately today a mostly manual task, and most scientists therefore do not take advantage of the faster storage media. One approach to systematically include node-local SSDs or NVRAMs into scientific workflows is to deploy ad hoc file systems over a set of compute nodes, which serve as temporary storage systems for single applications or longer-running campaigns. This paper presents results from the Dagstuhl Seminar 17202 "Challenges and Opportunities of User-Level File Systems for HPC" and discusses application scenarios as well as design strategies for ad hoc file systems using nodelocal storage media. The discussion includes open research questions, such as how to couple ad hoc file systems with the batch scheduling environment and how to schedule stage-in and stage-out processes of data between the storage backend and the ad hoc file systems. Also presented are strategies to build ad hoc file systems by using reusable components for networking and how to improve storage device compatibility. Various interfaces and semantics are presented, for example those used by the three ad hoc file systems BeeOND, GekkoFS, and BurstFS. Their presentation covers a range from file systems running in production to cutting-edge research focusing on reaching the performance limits of the underlying devices.

IBM Spectrum Scale’s parallel file system General Parallel File System (GPFS) has a 20-year development history with over 100 contributing developers. Its ability to support strict POSIX semantics across more than 10K clients leads to a complex design with intricate interactions between the cluster nodes. Tracing has proven to be a vital tool to understand the behavior and the anomalies of such a complex software product. However, the necessary trace information is often buried in hundreds of gigabytes of by-product trace records. Further, the overhead of tracing can significantly impact running applications and file system performance, limiting the use of tracing in a production system. In this research article, we discuss the evolution of the mature and highly scalable GPFS tracing tool and present the exploratory study of GPFS’ new tracing interface, FlexTrace , which allows developers and users to accurately specify what to trace for the problem they are trying to solve. We evaluate our methodology and prototype, demonstrating that the proposed approach has negligible overhead, even under intensive I/O workloads and with low-latency storage devices.

Many scientific fields increasingly use High-Performance Computing (HPC) to process and analyze massive amounts of experimental data while storage systems in today's HPC environments have to cope with new access patterns. These patterns include many metadata operations, small I/O requests, or randomized file I/O, while general-purpose parallel file systems have been optimized for sequential shared access to large files. Burst buffer file systems create a separate file system that applications can use to store temporary data. They aggregate node-local storage available within the compute nodes or use dedicated SSD clusters and offer a peak bandwidth higher than that of the backend parallel file system without interfering with it. However, burst buffer file systems typically offer many features that a scientific application, running in isolation for a limited amount of time, does not require. We present GekkoFS, a temporary, highly-scalable file system which has been specifically optimized for the aforementioned use cases. GekkoFS provides relaxed POSIX semantics which only offers features which are actually required by most (not all) applications. GekkoFS is, therefore, able to provide scalable I/O performance and reaches millions of metadata operations already for a small number of nodes, significantly outperforming the capabilities of common parallel file systems.

The need for parallel task execution has been steadily growing in recent years since manufacturers mainly improve processor performance by increasing the number of installed cores instead of scaling the processor's frequency. To make use of this potential, an essential technique to increase the parallelism of a program is to parallelize loops. Several automatic loop nest parallelizers have been developed in the past such as PluTo. The main restriction of these tools is that the loops must be statically analyzable which, among other things, disallows function calls within the loops. In this article, we present a seemingly simple extension to the C programming language which marks functions without side-effects. These functions can then basically be ignored when the automatic parallelizer checks the parallelizability of loops. We integrated the approach into the GCC compiler toolchain and evaluated it by running several real-world applications. Our experiments show that the C extension helps to identify additional parallelization opportunities and, thus, to significantly increase the performance of applications.