Intel
https://www.intel.com/content/www/us/en/products/programmable.html

インテルFPGAの利用は、altera時代を含め、あまりない。
　

fpga	intel	xininx
training	1	9
chip used	2	8
working time	1	99

Xilinx
https://www.xilinx.com/

インテルFPGAを使ったクラウドサービスを探したい。

まず、FPGAをクラウドで開発する環境を探し中。

cloud

3 Essential Considerations For FPGA Design In The Cloud
https://www.plunify.com/en/essential-considerations-fpga-design-cloud/

Designing for FPGAs in the Cloud, Naif Tarafdar, Nariman Eskandari, Thomas Lin, and Paul Chow University of Toronto
https://tarafdar.github.io/files/papers/2018-02-designing-for-fpgas-in-the-cloud.pdf

References
[1] Amazon Web Services Inc., Amazon Web Services,
2014. [Online]. Accessed: Nov. 16, 2016. Available:
http://aws.amazon.com
[2] J.-M. Kang et al., “SAVI testbed: Control and
management of converged virtual ICT resources,” in Proc. IFIP/IEEE Int. Symp. Integr. Network Management, 2013, pp. 664–667.
[3] A. Putnum et al., “A reconfigurable fabric for accelerating large-scale datacenter services,” in Proc. 2014 ACM/IEEE 41st Int. Symp. Comp. Architecture, 2014, pp. 13–24.
[4] O. Sefraoui et al., “OpenStack: Toward an open-source solution for cloud computing,” Int. J. Comp. Appl.,
vol. 55, no. 3, pp. 38–42, 2012.
[5] Xilinx Inc., SDAccel Development Environment, 2016. [Online]. Accessed: Nov. 12, 2016. Available: https:// www.xilinx.com/products/design-tools/software-zone/ sdaccel.html
[6] N. Tarafdar, T. Lin, E. Fukuda, H. Bannazadeh,
A. Leon-Garcia, and P. Chow, “Enabling flexible network FPGA clusters in a heterogenous cloud data center,” in Proc. Int. Symp. Field-Programmable Gate Arrays, 2017, pp. 237–246.
[7] N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford et al., “OpenFlow: Enabling innovation in campus networks,” in Proc. ACM SIGCOMM Comp. Commun. Rev., vol. 38, no. 2, pp. 69–74, 2008.
[8] S. Byma, N. Tarafdar, T. Xu, H. Bannazadeh,
A. Leon-Garcia, and P. Chow, “Expanding OpenFlow capabilities with virtualized reconfigurable hardware,” in Proc. FPGA ACM/SIGDA Int. Symp. Field- Programmable Gate Arrays, 2015, pp. 94–97.
[9] The Khronos Group, OpenCL Standard, 2015. [Online]. Available: https://www.khronos.org/opencl/
[10] IBM Research, OpenPOWER Cloud: Accelerating Cloud Computting, 2016. [Online]. Available: https:// www.research.ibm.com/labs/china/supervessel.html
[11] A. Caulfield et al., “A cloud-scale acceleration architecture,” in Proc. 49th Annu. IEEE/ACM Int. Symp. Microarchitecture, Oct. 2016, pp. 1–13.
[12] Amazon,AmazonEC2F1Instances,2016.[Online]. Available: https://aws.amazon.com/ec2/instance-types/f1/ [13] DPDKIntel,DataPlaneDevelopmentKit,2014.[Online].
Accessed October 12, 2016. Available: http://dpdk.org

Enabling FPGA-as-a-Service in the Cloud with hCODE Platform Qian ZHAO†a), Motoki AMAGASAKI†, Masahiro IIDA†, Morihiro KUGA†,

References
[1] M. Jacobsen, D. Richmond, M. Hogains, and R. Kastner, “RIFFA 2.1: A reusable integration framework for FPGA accelerators,” ACM Trans. Reconfigurable Technology and Systems, vol.8, no.4, Article No. 22, Oct. 2015.
[2] XILLYBUS Ltd., http://xillybus.com
[3] K. Vipin, S. Shreejith, D. Gunasekera, S.A. Fahmy, and N. Kapre,
“System-level FPGA device driver with high-level synthesis sup- port,” Proc. 2013 International Conference on Field Programmable Technology(ICFPT), pp.128–135, Dec. 2013.
[4] A. Putnam, A.M. Caulfield, E.S. Chung, D. Chiou, K. Constantinides, J. Demme, H. Esmaeilzadeh, J. Fowers, G.P. Gopal, J. Gray, M. Haselman, S. Hauck, S. Heil, A. Hormati, J.-Y. Kim, S. Lanka, J. Larus, E. Peterson, S. Pope, A. Smith, J. Thong, P.Y. Xiao, and D. Burger, “A reconfigurable fabric for accelerating large-scale datacenter services,” ACM/IEEE 41st International Symposium on Computer Architecture (ISCA), pp.13–24, June 2014.
[5] http://opencores.org
[6] https://cocoapods.org
[7] F. Chen, Y. Shan, Y. Zhang, Y. Wang, H. Franke, X. Chang, and K.
Wang, “Enabling FPGAs in the cloud,” Proc. 11th ACM Conference
on Computing Frontiers, Article No. 3, May 2014.
[8] S. Byma, J.G. Steffan, H. Bannazadeh, A.L. Garcia, and P. Chow, “FPGAs in the Cloud: Booting Virtualized Hardware Accelerators with OpenStack,” Proc. 22nd International Symposium on Field- Programmable Custom Computing Machines, pp.109–116, May
2014.
[9] J. Weerasinghe, F. Abel, C. Hagleitner, and A. Herkersdorf, “En-
abling FPGAs in Hyperscale Data Centers,” 2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communica- tions and Its Associated Workshops (UIC-ATC-ScalCom), pp.1078– 1086, Aug. 2015.
[10] M. Huang, D. Wu, C.H. Yu, Z. Fang, M. Interlandi, T. Condie, and J. Cong, “Programming and Runtime Support to Blaze FPGA Accel- erator Deployment at Datacenter Scale,” Proc. Seventh ACM Sym- posium on Cloud Computing, pp.456–469, Oct. 2016.
[11] A. Salah, http://opencores.org/project,aes-128 pipelined encryption, overview, June 2016.
[12] F. Winterstein, S. Bayliss, and G.A. Constantinides, “High-level synthesis of dynamic data structures: a case study using Vivado HLS,” Proc. International Conference on Field Programmable Tech- nology, pp.362–365, Dec. 2013.

おお、末吉さんの参加されている論文だ。　

STARC RTL 設計スタイルガイドに取り組みはじめたのは、末吉さんからの助言による。　

おかげさまで、自分の資料のslideshareに掲載している記事のうち、一番アクセスが多いのがFPGAです。　

slideshare top 10 on kaizenjapan(@kaizen_nagoya)
https://qiita.com/kaizen_nagoya/items/2035b961adad19b74c17

Cloud FPGA

FPGA designers turn to machine learning in the cloud
https://embeddedcomputing.com/technology/ai-machine-learning/fpga-designers-turn-to-machine-learning-in-the-cloud

参考資料　

RTL設計スタイルガイド Verilog HDL編
https://qiita.com/kaizen_nagoya/items/c883b9aab40c53c1d259

RTL設計スタイルガイド Verilog HDL編(System Verilog対応版）
https://qiita.com/kaizen_nagoya/items/4c02f1575db1f28310a7

FPGA と Verilog HDL
https://qiita.com/kaizen_nagoya/items/6db0b65fb1c227722660

＜この記事は書きかけです。順次追記します。＞

一覧

物理記事　上位100
https://qiita.com/kaizen_nagoya/items/66e90fe31fbe3facc6ff

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https://qiita.com/kaizen_nagoya/items/1cd954cb0eed92879fd4

数学関連記事１００
https://qiita.com/kaizen_nagoya/items/d8dadb49a6397e854c6d

統計(0)一覧
https://qiita.com/kaizen_nagoya/items/80d3b221807e53e88aba

言語・文学記事　１００
https://qiita.com/kaizen_nagoya/items/42d58d5ef7fb53c407d6

医工連携関連記事一覧
https://qiita.com/kaizen_nagoya/items/6ab51c12ba51bc260a82

自動車　記事　１００
https://qiita.com/kaizen_nagoya/items/f7f0b9ab36569ad409c5

通信記事１００
https://qiita.com/kaizen_nagoya/items/1d67de5e1cd207b05ef7

日本語（０）一欄
https://qiita.com/kaizen_nagoya/items/7498dcfa3a9ba7fd1e68

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https://qiita.com/kaizen_nagoya/items/680e3f5cbf9430486c7d

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https://qiita.com/kaizen_nagoya/items/f77520d378d33451d6fe

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鉄道（０）鉄道のシステム考察はてっちゃんがてつだってくれる
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https://qiita.com/kaizen_nagoya/items/7eb0e006543886138f39

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https://qiita.com/kaizen_nagoya/items/88d35e99f74aefc98794

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https://qiita.com/kaizen_nagoya/items/fbed841f61875c4731d0

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https://qiita.com/kaizen_nagoya/items/5e5464ac2b24bd4cd001

OSEK OS設計の基礎　OSEK(100)
https://qiita.com/kaizen_nagoya/items/7528a22a14242d2d58a3

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https://qiita.com/kaizen_nagoya/items/48b6cbc8d68eae2c42b8

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https://qiita.com/kaizen_nagoya/items/8720d26f762369a80514

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https://qiita.com/kaizen_nagoya/items/400725644a8a0e90fbb0

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なぜdockerで機械学習するか書籍・ソース一覧作成中 (目標100)
https://qiita.com/kaizen_nagoya/items/ddd12477544bf5ba85e2

言語処理100本ノックをdockerで。python覚えるのに最適。:10+12
https://qiita.com/kaizen_nagoya/items/7e7eb7c543e0c18438c4

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https://qiita.com/kaizen_nagoya/items/296d87ef4bfd516bc394

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https://qiita.com/kaizen_nagoya/items/088c57d70ab6904ebb53

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https://qiita.com/kaizen_nagoya/items/04ee6eaf7ec13d3af4c3

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https://qiita.com/kaizen_nagoya/items/2e41634f6e21a3cf74eb

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https://qiita.com/kaizen_nagoya/items/89c07961b59a8754c869

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https://qiita.com/kaizen_nagoya/items/9fe7c0dfac2fbd77a945

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https://qiita.com/kaizen_nagoya/items/e3f7dafacab58c499792

自動制御、制御工学一覧（０）
https://qiita.com/kaizen_nagoya/items/7767a4e19a6ae1479e6b

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https://qiita.com/kaizen_nagoya/items/5e8bb080ba6ca0281927

小川清最終講義、最終講義（再）計画, Ethernet(100) 英語(100) 安全(100)
https://qiita.com/kaizen_nagoya/items/e2df642e3951e35e6a53

＜この記事は個人の過去の経験に基づく個人の感想です。現在所属する組織、業務とは関係がありません。＞
This article is an individual impression based on the individual's experience. It has nothing to do with the organization or business to which I currently belong.

文書履歴(document history)

ver. 0.01初稿　20221223
ver. 0.02 ありがとう追記　20230701

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