Bibliographic record
Abstract
In this thesis, the Behrooz File System (BFS) is presented, which provides an in-memory distributed file system. BFS is a simple design which combines the best of in-memory and remote file systems. BFS stores data in the main memory of commodity servers and provides a shared unified file system view over them. BFS utilizes backend storage to provide persistency and availability. Unlike most existing distributed in-memory storage systems, BFS supports a general purpose POSIX-like file interface. BFS is built by grouping multiple servers’ memory together; therefore, if applications and BFS servers are co-located, BFS is a highly efficient design because this architecture minimizes inter-node communication. This pattern is common in distributed computing environments and data analytics applications. A set of microbenchmarks and SPEC SFS 2014 benchmark are used to evaluate different aspects of BFS, such as throughput, reliability, and scalability. The evaluation results indicate the simple design of BFS is successful in delivering the expected performance, while certain workloads reveal limitations of BFS in handling a large number of files. Addressing these limitations, as well as other potential improvements, are considered as future work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".