Catalytic computing, a new theoretical framework, aims to overcome the limitations of traditional computing by leveraging the entire storage capacity of a device, such as a hard drive, for computation. Instead of relying on limited working memory, catalytic computing treats the entire memory system as a catalyst, allowing data to transform itself through local interactions within the storage itself. This approach, inspired by chemical catalysts, could drastically expand the complexity and scale of computations possible, potentially enabling the efficient processing of massive datasets that are currently intractable for conventional computers. While still theoretical, catalytic computing represents a fundamental shift in thinking about computation, promising to unlock the untapped potential of existing hardware.
Backblaze's 2024 hard drive stats reveal a continued decline in annualized failure rates (AFR) across most drive models. The overall AFR for 2024 was 0.83%, the lowest ever recorded by Backblaze. Larger capacity drives, particularly 16TB and larger, demonstrated remarkably low failure rates, with some models exhibiting AFRs below 0.5%. While some older drives experienced higher failure rates as expected, the data suggests increasing drive reliability overall. Seagate drives dominated Backblaze's data centers, comprising the majority of drives and continuing to perform reliably. The report highlights the ongoing trend of larger drives becoming more dependable, contributing to the overall improvement in data storage reliability.
Hacker News users discuss Backblaze's 2024 drive stats, focusing on the high failure rates of WDC drives, especially the 16TB and 18TB models. Several commenters question Backblaze's methodology and data interpretation, suggesting their usage case (consumer drives in enterprise settings) skews the results. Others point out the difficulty in comparing different drive models directly due to varying usage and deployment periods. Some highlight the overall decline in drive reliability and express concerns about the industry trend of increasing capacity at the expense of longevity. The discussion also touches on SMART stats, RMA processes, and the potential impact of SMR technology. A few users share their personal experiences with different drive brands, offering anecdotal evidence that contradicts or supports Backblaze's findings.
Reports are surfacing about new Seagate hard drives, predominantly sold through Chinese online marketplaces, exhibiting suspiciously long power-on hours and high usage statistics despite being advertised as new. This suggests potential fraud, where used or refurbished drives are being repackaged and sold as new. While Seagate has acknowledged the issue and is investigating, the extent of the problem remains unclear, with speculation that the drives might originate from cryptocurrency mining operations or other data centers. Buyers are urged to check SMART data upon receiving new Seagate drives to verify their actual usage.
Hacker News users discuss potential explanations for unexpectedly high reported runtime hours on seemingly new Seagate hard drives. Some suggest these drives are refurbished units falsely marketed as new, with inflated SMART data to disguise their prior use. Others propose the issue stems from quality control problems leading to extended testing periods at the factory, or even the use of drives in cryptocurrency mining operations before being sold as new. Several users share personal anecdotes of encountering similar issues with Seagate drives, reinforcing suspicion about the company's practices. Skepticism also arises about the reliability of SMART data as an indicator of true drive usage, with some arguing it can be manipulated. Some users suggest buying hard drives from more reputable retailers or considering alternative brands to avoid potential issues.
Summary of Comments ( 15 )
https://news.ycombinator.com/item?id=43091159
Hacker News users discussed the potential and limitations of catalytic computing. Some expressed skepticism about the practicality and scalability of the approach, questioning the overhead and energy costs involved in repeatedly reading and writing data. Others highlighted the potential benefits, particularly for applications involving massive datasets that don't fit in RAM, drawing parallels to memory mapping and virtual memory. Several commenters pointed out that the concept isn't entirely new, referencing existing techniques like using SSDs as swap space or leveraging database indexing. The discussion also touched upon the specific use cases where catalytic computing might be advantageous, like bioinformatics and large language models, while acknowledging the need for further research and development to overcome current limitations. A few commenters also delved into the theoretical underpinnings of the concept, comparing it to other computational models.
The Hacker News thread discussing the Quanta Magazine article "Catalytic computing taps the full power of a full hard drive" contains several interesting comments exploring the potential and limitations of the proposed catalytic computing paradigm.
Several commenters express excitement about the potential of catalytic computing to revolutionize data processing by enabling the use of all data stored on a hard drive simultaneously. They see this as a potential game-changer for fields dealing with massive datasets, like genomics and machine learning. The analogy to chemical reactions, where a catalyst facilitates a process without being consumed, is seen as a compelling and potentially fruitful way to rethink computation.
Some commenters delve into the technical aspects of the proposed system. One commenter questions the practical feasibility of achieving simultaneous access to all data on a hard drive, pointing out physical limitations like read/write head speed and data bus bandwidth. This leads to a discussion about the possible need for novel hardware architectures and data storage mechanisms to truly realize the vision of catalytic computing. Another comment explores the potential connection between catalytic computing and existing concepts like in-memory computing and distributed systems, suggesting that catalytic computing might represent a novel combination or extension of these ideas.
A few commenters express skepticism about the scalability and practicality of the proposed approach. They raise concerns about the potential energy consumption of such a system, particularly if it involves simultaneous access to all data on a large hard drive. The potential for noise and interference in a system with so many simultaneous operations is also mentioned as a potential challenge.
There's also a discussion about the potential applications of catalytic computing beyond the examples mentioned in the article. One commenter suggests its potential use in cryptography, particularly for breaking current encryption methods. Another commenter speculates on its application in areas like artificial intelligence and drug discovery.
Finally, some commenters express a desire for more technical details about the proposed catalytic computing system. They request more information about the specific mechanisms for data access, the nature of the "catalysts," and the expected performance characteristics of such a system. They suggest that a deeper understanding of these technical details is essential for assessing the true potential and limitations of catalytic computing.