RISC-V NaN Generation and Propagation

1. RISC-V spec said NaN propagation should generate canonical NaN

Except when otherwise stated, if the result of a floating-point operation is NaN, it is the canonical NaN. The canonical NaN has a positive sign and all significand bits clear except the MSB, a.k.a. the quiet bit. For single-precision floating-point, this corresponds to the pattern 0x7fc00000.

2. IEEE 754 2018 standard recommends that operations on NaNs could propagate the input's NaN, but it's not required.

3. LLVM NaN propagation implementation follows IEEE rule which does not match RISC-V spec.

https://github.com/llvm/llvm-project/blob/main/llvm/lib/Analysis/InstructionSimplify.cpp#L4966-L4968


The simplest test is adding two constant floating values and one is NaN, and the result of  -O0 and -O3 are different due to the NaN's fraction bit.

So software could use C++ isnan() to check NaN before comparing, it's why we could not use memcmp to compare two floating values, not only accuracy issue, but also non-portable.

BTW, I don't like spec giving a recommended rule...

留言

張貼留言

這個網誌中的熱門文章

我們能利用machine learning去幫助compiler的optimization演算法變強嗎？

ML通常是拿來幫忙做predict和decisions 透過大量training data  (input: feature,  output: predict a value or classification) 對於沒有看過的feature做predict和decisio ns 我對於ML經驗只有半年多 以下是我的一些看法 1.  如果是對特定benchmark的話 用ML能幫忙找出不錯的heuristic值 (ex.  --param,  --regalloc=[ basic|fast|greedy|pbqp] 等等) google也滿多的 Automatic Feature Generation for Machine Learning Based Optimizing Compilation 但直到看到"MILEPOST GCC"  覺得圖很眼熟... 就是interactive compiler! 2.  如果想把machine learning的training也做進compiler內 看來就只能做在JIT了 google了一下也有人做到VM Using machines to learn method-specific compilation strategies (IBM) Method-Specific Dynamic Compilation using Logistic Regression 也有人拿來做CPU/GPU decisions XD Machine-Learning-based Performance Heuristics for Runtime CPU/GPU Selection 如果做在AOT compiler, 感覺就像PGO, 看起來也不需ML 3.  如果要用machine learning去學出某隻benchmark/ function最好的instruction sequence 感覺可以用reinforcement learning去做 但是用interactive compiler去挑heuristic就可能做...
閱讀完整內容

The Speed Game: Automated Trading Systems in C++

https://meetingcpp.com/index.php/tv16/items/18.html C++ low latency coding techniques： ● General considerations C++11 Move semantics Static assert Data member layout, padding and alignment (盡量alignment access) ● False sharing http://shuyufu.blogspot.tw/2013/01/false-sharing.html ● Cache locality ● Compile-time dispatch std::sort(array, array + N, []( int a, int b) { return b < a; });  71us, std deviation 1.5us int comparer( const void * a, const void* b) { return *(int*)a - *(int*)b; } qsort(arr, N, sizeof(int), comparer); 223us, std deviation 7us ● Constexpr C++14 feature ● Variadic templates ● Loop unrolling Generally, don’t bother, the compiler will figure it out ● Expression short-circuiting Rewrite: if (expensiveCheck() && inexpensiveCheck()) {} As: if (inexpensiveCheck() && expensiveCheck()) {} ● Signed vs unsigned comparisons 用loop iteratort用signed就是了 （可看前篇 ● Mixing float and doubles Default type of a floating...
閱讀完整內容

被討厭的勇氣 自我啟發之父阿德勒的教導

重點在於並不是因為發生了這些事就一定有什麼樣的結果, 我們是藉著"賦予過去的經驗什麼意義"來決定自己的一生. 人生不是別人給的,是我們自己選擇的. 決定要怎麼生活的, 是我們自己 問題不是在"經歷什麼事", 而是"如何解釋它", "如何運用它" 無論之前你的人生發生過什麼事, 那對你將來要怎麼過日子一點影響也沒有. 決定你人生的, 是活在當下的自己 我們無法改變客觀的事實, 卻可以隨意更改主觀的解釋 憤怒不過是一種為了達到目的而採取的手段,只是個工具而已 老是想要尋求別人的認同,在意他人的評價,到最後你過的就是別人的人生 完全只在乎"別人是如何看我"的這種生活方式,其實正是以自我為中心,只關心"我"的生活型態  ==>  你都沒想到 因為你只想到你自己
閱讀完整內容