The blog post details the creation of an extremely fast phrase search algorithm leveraging the AVX-512 instruction set, specifically the VPCONFLICTM instruction. This instruction, designed to detect hash collisions, is repurposed to efficiently find exact occurrences of phrases within a larger text. By cleverly encoding both the search phrase and the text into a format suitable for VPCONFLICTM, the algorithm can rapidly compare multiple sections of the text against the phrase simultaneously. This approach bypasses the character-by-character comparisons typical in other string search methods, resulting in significant performance gains, particularly for short phrases. The author showcases impressive benchmarks demonstrating substantial speed improvements compared to existing techniques.
The blog post argues that C's insistence on abstracting away hardware details makes it poorly suited for effectively leveraging SIMD instructions. While extensions like intrinsics exist, they're cumbersome, non-portable, and break C's abstraction model. The author contends that higher-level languages, potentially with compiler support for automatic vectorization, or even assembly language for critical sections, would be more appropriate for SIMD programming due to the inherent need for data layout awareness and explicit control over vector operations. Essentially, C's strengths become weaknesses when dealing with SIMD, hindering performance and programmer productivity.
Hacker News users discussed the challenges of using SIMD effectively in C. Several commenters agreed with the author's point about the difficulty of expressing SIMD operations elegantly in C and how it often leads to unmaintainable code. Some suggested alternative approaches, like using higher-level languages or libraries that provide better abstractions, such as ISPC. Others pointed out the importance of compiler optimizations and using intrinsics effectively to achieve optimal performance. One compelling comment highlighted that the issue isn't inherent to C itself, but rather the lack of suitable standard library support, suggesting that future additions to the standard library could mitigate these problems. Another commenter offered a counterpoint, arguing that C's low-level nature is exactly why it's suitable for SIMD, giving programmers fine-grained control over hardware resources.
Summary of Comments ( 11 )
https://news.ycombinator.com/item?id=42808355
Several Hacker News commenters express skepticism about the practicality of the described AVX-512 phrase search algorithm. Concerns center around the limited availability of AVX-512 hardware, the potential for future deprecation of the instruction set, and the complexity of the code making it difficult to maintain and debug. Some question the benchmark methodology and the real-world performance gains compared to simpler SIMD approaches or existing optimized libraries. Others discuss the trade-offs between speed and portability, suggesting that the niche benefits might not outweigh the costs for most use cases. There's also a discussion of alternative approaches and the potential for GPUs to outperform CPUs in this task. Finally, some commenters express fascination with the cleverness of the algorithm despite its practical limitations.
The Hacker News post discussing the article "Using the most unhinged AVX-512 instruction to make the fastest phrase search algo" has generated a moderate number of comments, exploring various aspects of the approach and its implications.
Several commenters focus on the practicality and limitations of relying on AVX-512. One commenter points out the limited availability of AVX-512, restricting its use to specific, newer Intel CPUs, and raises concerns about power consumption. This commenter also questions the real-world performance gains, suggesting that the optimization might not be significant enough to justify the hardware requirements. Another echoes this sentiment, highlighting the trade-off between specialized hardware and wider applicability. The discussion extends to the broader context of SIMD instructions, with one commenter mentioning that even AVX2 can be challenging to utilize effectively due to its complexity and the need for specific data layouts.
The conversation also delves into the technical details of the algorithm itself. One commenter questions the claim of being the "fastest" and inquires about benchmarks comparing it to existing solutions. There's discussion about the specific AVX-512 instruction used (_mm512_mask_compress_epi64), with a commenter explaining its functionality and how it contributes to the algorithm's performance. Another user delves deeper into the vectorization approach, speculating on potential improvements and limitations when dealing with variable-length phrases.
Beyond performance, the maintainability and complexity of the code are also discussed. One commenter expresses concern about the readability and debuggability of code heavily reliant on SIMD intrinsics. Another suggests that simpler approaches, while potentially slightly slower, might be preferable in many scenarios due to their easier implementation and maintenance.
Finally, the conversation touches upon alternative approaches to phrase searching, such as suffix arrays and FM-indexes, comparing their characteristics to the vectorized approach presented in the article. One commenter suggests exploring these alternative methods for potentially better performance or broader applicability.
While there isn't a single overwhelmingly compelling comment, the collection of comments provides valuable perspectives on the trade-offs involved in utilizing advanced SIMD instructions for specific tasks like phrase searching. The discussion highlights the importance of considering factors beyond raw performance, including hardware limitations, code complexity, and the availability of alternative solutions.