NNBlocks: a Blockly framework for AI computing

Chen, Tai‐Liang; Chen, Yi-Ru; Yu, Meng-Shiun; Lee, Jenq-Kuen

doi:10.1007/s11227-021-03631-9

Cited by 6 publications

(3 citation statements)

References 37 publications

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“…TVM [12] is an end-to-end machine learning compiler framework for CPUs, GPUs, and accelerators. It is an intermediary platform that can integrate various applications and systems, including blockly applications [13], runtime support for Android NNAPI [14], compiler optimizations across many machine learning computers [15] and underlying integration with a GPU [16], [17]. Fig.…”

Section: Background a Tvm And Hybrid Scriptmentioning

confidence: 99%

Case Study: Optimization Methods With TVM Hybrid-OP on RISC-V Packed SIMD

Yu,

Yuan,

Chen

et al. 2024

IEEE Access

Self Cite

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In recent years, considerable research has focused on the use of custom hardware to accelerate deep learning on edge devices. However, the end-to-end flow of deep learning includes preprocessing and postprocessing. Deep learning hardware accelerators cannot accelerate these operations, which consequently becomes a performance bottleneck in the execution flow. In this study, we propose optimization methods to improve preprocessing and postprocessing at the edge devices. For this purpose, we adopt Tensor Virtual Machine (TVM), an end-to-end machine learning compiler framework. TVM provides hybrid script, which is a frontend language that allows users to write programs for preprocessing and postprocessing. We propose rewriting strategies to improve the performance of operators written in hybrid script through the RISC-V Packed SIMD extension (P extension). RISC-V is an open instruction set architecture (ISA) that provides base instructions and many extensions for different use cases. The P extension defines specific subword single-instruction multiple-data (SIMD) instructions that allow complex computations to be efficiently performed on edge devices. In this study, we design custom instructions based on the RISC-V P extension for rewriting strategies to accelerate deep learning operations. Experimental results indicate that our methods improve performance by a factor of 1.28 to 15.29.

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Section: Background a Tvm And Hybrid Scriptmentioning

confidence: 99%

Case Study: Optimization Methods With TVM Hybrid-OP on RISC-V Packed SIMD

Yu,

Yuan,

Chen

et al. 2024

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

“…This enables students to focus on programming logic (López et al, 2021). These features of Blockly reduce the complexity of programming and facilitate beginner programmers to learn the programming languages (Chen et al, 2021;Rahaman et al, 2020;Sano & Kagawa, 2019;Winterer et al, 2020). According to Adi and Kitagawa (2019), Blockly is a convenient environment for novice programmers to start learning Python programming language.…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies are mostly in the engineering field, and on the usability of a technological system developed using Blockly (Adi & Kitagawa, 2019;Bak, Chang, & Choi, 2020;Chen, Chen, Yu, & Lee, 2021;Ionescu, 2021;Jung et al, 2021;Rahaman et al, 2020;Rodríguez-Gil et al, 2019;Weintrop, Shepherd, Francis, & Franklin, 2017;Winterer, Salomon, Köberle, Ramler, & Schittengruber, 2020). There are also available studies using Blockly in programming education at different grade levels.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Case Study to Experiences of High School Students Using Text-Based versus Hybrid-Based Environments in Programming Education

Suderman

Topu

2022

E-Kafkas Eğitim Araştırmaları Dergisi

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This study aims to comparatively determine the experiences of high school students in programming language education via Python editor or Blockly tool. The comparative case study was conducted in this study. The participants consisted of total 19 high school students with no previous experience on any programming language, 9 of them in Python editor group and 10 of them in Blockly tool group. The qualitative data obtained with a semi-structured interview at the end of 10-week programming education process and analyzed by content analysis. The findings was presented in dimensions of programming process, course outcomes, and future programming courses. In each dimension, even if common codes obtained for both groups in some themes, the effects of these codes on students differed in each group. According to results, in the programming process, students faced some difficulties and conveniences in terms of mental effort. Some situations caused the learning anxiety in students, while others did not. The students achieved positive and negative course outcomes. In addition, students' preferences whether or not to attend the future programming courses changed for various reasons. Considering the scarcity of programming education studies via Python editor and Blockly tool, the results and implications of this study will strengthen future research by providing the rich data.

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Case Study: Design Strategies for Enabling Visual Application Blocks of Bluetooth Library

Chen

Lee

2022

IEEE Access

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NNBlocks: a Blockly framework for AI computing

Cited by 6 publications

References 37 publications

Case Study: Optimization Methods With TVM Hybrid-OP on RISC-V Packed SIMD

Case Study: Optimization Methods With TVM Hybrid-OP on RISC-V Packed SIMD

A Comparative Case Study to Experiences of High School Students Using Text-Based versus Hybrid-Based Environments in Programming Education

Case Study: Design Strategies for Enabling Visual Application Blocks of Bluetooth Library

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