Applications are migrating en masse to the cloud, while accelerators such as GPUs, TPUs, and FPGAs proliferate in the wake of Moore's Law. These trends are in conflict: cloud applications run on virtual platforms, but existing virtualization techniques have not provided production-ready solutions for accelerators. As a result, cloud providers expose accelerators by dedicating physical devices to individual guests. Multi-tenancy and consolidation are lost as a consequence.

Applications are migrating en masse to the cloud, while accelerators such as GPUs, TPUs, and FPGAs proliferate in the wake of Moore's Law. These technological trends are incompatible. Cloud applications run on virtual platforms, but traditional I/O virtualization techniques have not provided production-ready solutions for accelerators. As a result, cloud providers expose accelerators by using pass-through techniques which dedicate physical devices to individual guests. The multi-tenancy that drives their business is lost as a consequence.

This paper presents a study of x86-64 instruction usage across 9,337 C/C++ applications and libraries in the Ubuntu 16.04 GNU/Linux distribution. We present metrics for reasoning about the relative importance of instructions weighted by the popularity of applications that contain them. From this data, we systematize and empirically ground conventional wisdom regarding the relative importance of various components of an ISA, with particular focus on building binary translation tools. We also verify the representativity of two commonly used benchmark suites, and highlight areas for improvement.

File systems that employ write-optimized dictionaries (WODs) can perform random-writes, metadata updates, and recursive directory traversals orders of magnitude faster than conventional file systems. However, previous WOD-based file systems have not obtained all of these performance gains without sacrificing performance on other operations, such as file deletion, file or directory renaming, or sequential writes. Using three techniques, late-binding journaling , zoning , and range deletion , we show that there is no fundamental trade-off in write-optimization. These dramatic improvements can be retained while matching conventional file systems on all other operations. BetrFS 0.2 delivers order-of-magnitude better performance than conventional file systems on directory scans and small random writes and matches the performance of conventional file systems on rename, delete, and sequential I/O. For example, BetrFS 0.2 performs directory scans 2.2 × faster, and small random writes over two orders of magnitude faster, than the fastest conventional file system. But unlike BetrFS 0.1, it renames and deletes files commensurate with conventional file systems and performs large sequential I/O at nearly disk bandwidth. The performance benefits of these techniques extend to applications as well. BetrFS 0.2 continues to outperform conventional file systems on many applications, such as as rsync, git-diff, and tar, but improves git-clone performance by 35% over BetrFS 0.1, yielding performance comparable to other file systems.

The B ε -tree File System , or B e trFS (pronounced “better eff ess”), is the first in-kernel file system to use a write-optimized data structure (WODS). WODS are promising building blocks for storage systems because they support both microwrites and large scans efficiently. Previous WODS-based file systems have shown promise but have been hampered in several ways, which B e trFS mitigates or eliminates altogether. For example, previous WODS-based file systems were implemented in user space using FUSE, which superimposes many reads on a write-intensive workload, reducing the effectiveness of the WODS. This article also contributes several techniques for exploiting write-optimization within existing kernel infrastructure. B e trFS dramatically improves performance of certain types of large scans, such as recursive directory traversals, as well as performance of arbitrary microdata operations, such as file creates, metadata updates, and small writes to files. B e trFS can make small, random updates within a large file 2 orders of magnitude faster than other local file systems. B e trFS is an ongoing prototype effort and requires additional data-structure tuning to match current general-purpose file systems on some operations, including deletes, directory renames, and large sequential writes. Nonetheless, many applications realize significant performance improvements on B e trFS. For instance, an in-place rsync of the Linux kernel source sees roughly 1.6--22 × speedup over commodity file systems.