This paper presents an analysis of how Linux's performance has evolved over the past seven years. Unlike recent works that focus on OS performance in terms of scalability or service of a particular workload, this study goes back to basics: the latency of core kernel operations (e.g., system calls, context switching, etc.). To our surprise, the study shows that the performance of many core operations has worsened or fluctuated significantly over the years. For example, the select system call is 100% slower than it was just two years ago. An in-depth analysis shows that over the past seven years, core kernel subsystems have been forced to accommodate an increasing number of security enhancements and new features. These additions steadily add overhead to core kernel operations but also frequently introduce extreme slowdowns of more than 100%. In addition, simple misconfigurations have also severely impacted kernel performance. Overall, we find most of the slowdowns can be attributed to 11 changes. Some forms of slowdown are avoidable with more proactive engineering. We show that it is possible to patch two security enhancements (from the 11 changes) to eliminate most of their overheads. In fact, several features have been introduced to the kernel unoptimized or insufficiently tested and then improved or disabled long after their release. Our findings also highlight both the feasibility and importance for Linux users to actively configure their systems to achieve an optimal balance between performance, functionality, and security: we discover that 8 out of the 11 changes can be avoided by reconfiguring the kernel, and the other 3 can be disabled through simple patches. By disabling the 11 changes with the goal of optimizing performance, we speed up Redis, Apache, and Nginx benchmark workloads by as much as 56%, 33%, and 34%, respectively.

In this article, we survey existing academic and commercial efforts to provide Field-Programmable Gate Array (FPGA) acceleration in datacenters and the cloud. The goal is a critical review of existing systems and a discussion of their evolution from single workstations with PCI-attached FPGAs in the early days of reconfigurable computing to the integration of FPGA farms in large-scale computing infrastructures. From the lessons learned, we discuss the future of FPGAs in datacenters and the cloud and assess the challenges likely to be encountered along the way. The article explores current architectures and discusses scalability and abstractions supported by operating systems, middleware, and virtualization. Hardware and software security becomes critical when infrastructure is shared among tenants with disparate backgrounds. We review the vulnerabilities of current systems and possible attack scenarios and discuss mitigation strategies, some of which impact FPGA architecture and technology. The viability of these architectures for popular applications is reviewed, with a particular focus on deep learning and scientific computing. This work draws from workshop discussions, panel sessions including the participation of experts in the reconfigurable computing field, and private discussions among these experts. These interactions have harmonized the terminology, taxonomy, and the important topics covered in this manuscript.

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a través de un modelo de regresión logística para una universidad en Bogotá, Colombia* Work environment evaluation methodology through a logistic regression model for a university in Bogota, Colombia.

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