Challenge your understanding of input/output performance optimization with these medium-difficulty questions. Enhance your knowledge of techniques, key concepts, and pitfalls in efficient I/O management for better system performance.
Which approach is most effective for minimizing disk access time when reading large files sequentially?
Explanation: Configuring a large read buffer allows more data to be read in each operation, reducing the total number of disk accesses and improving performance for sequential file reading. Random access for every block increases seek times and degrades efficiency. Using a very small buffer causes frequent disk access and overhead. Flushing buffers after every read is unnecessary in sequential reading and can actually slow down performance.
Why does implementing asynchronous I/O often increase throughput in applications that process multiple I/O operations concurrently?
Explanation: Asynchronous I/O lets the CPU perform other tasks while waiting for slower I/O operations to finish, increasing overall throughput. Sequential completion would slow down the application, which is what happens in synchronous I/O. Increased hardware bandwidth is not guaranteed by software-level changes. Data buffering is still necessary for handling partial results, so eliminating buffering is not a benefit.
In the context of improving both I/O performance and reliability, which RAID configuration is best suited for a workload requiring both fast data access and redundancy?
Explanation: RAID 10 combines striping, which increases speed, and mirroring, which provides redundancy, making it suitable for workloads needing both performance and reliability. RAID 0 offers no redundancy and only improves speed. RAID 1 gives redundancy but no boost in throughput. 'RAIS 0' is a typographical error and not a valid configuration.
How does heavy file system fragmentation negatively affect I/O performance during large file reads?
Explanation: File system fragmentation scatters file data across multiple locations, requiring the disk head to move more frequently and increasing seek times, which slows down performance. File systems do not automatically compress files due to fragmentation. CPU utilization may indirectly rise, but the primary effect is on disk seek time. Fragmentation does not prevent all caching; caches may be less effective, but not disabled.
When optimizing I/O-bound applications, which strategy best leverages modern multi-core architectures for faster data transfer?
Explanation: Distributing I/O tasks among several threads or processes allows simultaneous operations, better utilizing multiple cores and improving throughput. Reducing to one thread limits parallelism and potential speedup. Disabling prefetching can decrease performance by removing predictive reading capabilities. Lowering thread priority may cause I/O tasks to wait unnecessarily, reducing efficiency.