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On the New Era of Computing

Agenda

the brain

  • what our brain is?
  • ~1.3 square, ~100B neurons in adult human brain
  • eg., some works from a berkeley lab

neuron morphological computing, //bio-mimic

Computational model from typical computer scientist's eyes

the deep revolution, started by Geoffrey Hinton

  • works back from 30 years ago
  • Canada ppl
  • how to deep
  • e.g., Networks, Representations, Visual Cortex, ,
  • history of the Hinton family

Hardware deep learning accelerator (on chip)

  • the ending Moore's law for tuning machine (or say von Neumann machine), e.g.
  • ,
  • end of down-scale, high clock frequency, power consuming
  • the efficiency of silicon footprint
  • CPU/SIMD/GPU/FPGA/deep learning accelerator?
  • Emergence in the silicon world
  • the biggest acquiration in history for Intel, Intel acquired Altera
  • CAS Diannao, DaDiannao series
  • Horizontal Tech, by Kai Yu, Ex-Baiduer, the former leader of Baidu IDL
  • the Synopsys IP
  • Mobileye
  • to name a few //other vendors/projects
  • review, the singularity metaphor of computation capacity, new era for computation, the left/right brain for silicon

What we can do from now, and here (eg., XCJ)

Thanks

##--

Appendix

two fundamental problem on theoritical computer science

  • computational complexity (mostly on model of tuning machine or likely)
  • artificial intelligence
  • 它的平均性能（TOPS）可以达到CPU和GPU的15到30倍，能耗效率（TOPS/W）能到30到80倍。如果使用GPU的DDR5 memory，这两个数值可以达到大约GPU的70倍和CPU的200倍。[Google TPU 揭密, StarryHeavensAbove]
  • MLU100 采用寒武纪最新的 MLUv01 架构和 TSMC 16nm 工艺，可工作在平衡模式（主频 1Ghz）和高性能模式（1.3GHz）主频下，等效理论峰值速度则分别可以达到 128 万亿次定点运算/166.4 万亿次定点运算，而其功耗为 80w/110w
  • groq: 400TOP/s的性能指标，8TOP/s/W的能效指标
  • groq
  • [Vathys] Asynchronous Logic, High-density Memory, Wireless 3D stacking: 1PetaFLOPs
  • Vathys: 1PetaFLOPs
  • 如何设计一颗40PFLOPS量级的AI芯片？
  • Hennessy and Patterson
  • 2018-02-05，Google 的母公司 Alphabet 宣布 John Hennessy 将接替 Eric Schimdt 就任董事长。而在这之前，David Patterson 就已经开始在 Google 担任杰出工程师
  • RISC-V与DSA！ 计算机架构宗师Patterson与Hennessy 演讲实录
  • 2017年图灵奖颁给计算机体系结构大师Hennessy和Patterson

Reference

  • --

Some proposal：

  • 图灵计算与深度计算，硅上的左脑与右脑*

关键词摘要（其实我更愿意作为标题）：

  • 脑，神经认知计算与硅实现，深度学习，深度硬件加速器，以及在新车间我们能够干嘛

|| *左右脑这个称呼并不精确，但是鉴于这个被误用的概念为人们熟知所以在这里作为一个隐喻

报告材料没做完，也可能就这么用 -