LoopTune: Optimizing Tensor Computations with Reinforcement Learning

Advanced compiler technology is crucial for enabling machine learning applications to run on novel hardware, but traditional compilers fail to deliver performance, popular auto-tuners have long search times and expert-optimized libraries introduce unsustainable costs. To address this, we developed LoopTune, a deep reinforcement learning compiler that optimizes tensor computations in deep learning models for the CPU. LoopTune optimizes tensor traversal order while using the ultra-fast lightweight code generator LoopNest to perform hardware-specific optimizations. With a novel graph-based representation and action space, LoopTune speeds up LoopNest by 3.2x, generating an order of magnitude faster code than TVM, 2.8x faster than MetaSchedule, and 1.08x faster than AutoTVM, consistently performing at the level of the hand-tuned library Numpy. Moreover, LoopTune tunes code in order of seconds

Large Language Models for Compiler Optimization

We explore the novel application of Large Language Models to code optimization. We present a 7B-parameter transformer model trained from scratch to optimize LLVM assembly for code size. The model takes as input unoptimized assembly and outputs a list of compiler options to best optimize the program. Crucially, during training, we ask the model to predict the instruction counts before and after optimization, and the optimized code itself. These auxiliary learning tasks significantly improve the optimization performance of the model and improve the model's depth of understanding. We evaluate on a large suite of test programs. Our approach achieves a 3.0% improvement in reducing instruction counts over the compiler, outperforming two state-of-the-art baselines that require thousands of compilations. Furthermore, the model shows surprisingly strong code reasoning abilities, generating compilable code 91% of the time and perfectly emulating the output of the compiler 70% of the time

Gibberellic acid nitrite stimulates germination of two species of light-requiring seeds via the nitric oxide pathway

We used two species of light-requiring seeds, Paulownia tomentosa, which have absolute light requirement (no germination in darkness), and Stellaria media seeds, which germinate in darkness to a certain extent because of presence of preformed active phytochrome, to obtain results strongly suggesting that gibberellic acid nitrite stimulates seed germination via its capability as a functional NO donor. Exogenous application of gibberellic acid nitrite stimulates gibberellin-insensitive Stellaria media seed germination in darkness as do a wide variety of NO donors. Pure gibberellic acid could replace the light requirement of P tomentosa seeds, thus enabling them to germinate in darkness. Gibberellic acid nitrite did not have this effect. A stimulative effect from gibberellic acid nitrite could be detected only after exposure of these seeds to short, 10 min, pulse of red light. Taken together, these results suggest that gibberellic activity of gibberellic acid nitrite is lost after nitrosation but, regarding to the presence of -O-NO moiety in the molecule, gibberellic acid nitrite shares stimulative properties in seed germination with other compounds with NO-releasing properties

Essential oil of achillea corabensis (heimerl) micevski

The essential oil of Achillea corabensis (Heimerl) Micevski collected from a natural location as well as from plants cultivated in the Sirinic valley of Sara mountain was analyzed. In the oil of collected plants 41 compounds were identified, while in the oil from the cultivated plants 36 compounds were identified. In the oil obtained from plants harvested in the wild the monoterpene fraction represented 88.0% of the whole oil, whereas the sesquiterpene fraction represented 5.9% and other compounds 3.1% of the total oil composition. In the oil of cultivated plants, the monoterpene fraction represented 74.6%, the sesquiterpene fraction 10.2% and other compounds 3.5% of the oil composition. In both cases the most abundant compounds were sabinene (33% and 25%) and p-cymene (29–4% and 17%). © 1997, Taylor & Francis Group, LLC. All rights reserved