Skip to main content
SpringerLink
Log in

Bitcoin Mining Using Maxeler DataFlow Computers

  • Chapter
  • First Online:
Exploring the DataFlow Supercomputing Paradigm

Part of the book series: Computer Communications and Networks ((CCN))

  • 501 Accesses

Abstract

Bitcoin, which is known as the world’s first decentralized peer-to-peer payment network and cryptocurrency, introduced a decentralized mining process, where miners compete in confirming transactions in order to earn a certain amount of digital coins (bitcoins). Bitcoin mining is a repetitive and highly parallelizable process, and thus suitable for parallel computing. In this chapter, we present Maxeler dataflow paradigm as a form of parallel computing to process big data with low energy consumption and explain our dataflow implementation of the bitcoin mining algorithm for Maxeler MAX2B and MAX5C dataflow computers. With our dataflow design, we achieved up to 102 times faster and up to 256 times more energy-efficient bitcoin mining compared to standard multicore CPUs (Central Processing Units). While Maxeler dataflow computers are not able to compete against ASIC (Application-Specific Integrated Circuit) bitcoin mining rigs in terms of hash rate and energy efficiency, they are flexible and can be reprogrammed to do other tasks, while ASIC mining rigs are fixed (running only one specific algorithm) and usually become outdated in a few months.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 59.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 59.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Nakamoto S (2008) Bitcoin: a peer-to-peer electronic cash system. Available https://bitcoin.org/bitcoin.pdf. Accessed 1 July 2017 (Online)

  2. Antonopoulos A (2015) Mastering bitcoin: unlocking digital cryptocurrencies. O’Reilly Media, Sebastopol

    Google Scholar 

  3. Blagojević V et al (2016) A systematic approach to generation of new ideas for PhD research in computing. Adv Comput 104:1–19 Elsevier

    Google Scholar 

  4. Apps|Maxeler AppGallery. Available http://appgallery.maxeler.com/. Accessed 1 July 2017 (Online)

  5. Trifunović N, Milutinović V, Korolija N, Gaydadjiev G (2016) An AppGallery for dataflow computing. J Big Data 3(1):4

    Article  Google Scholar 

  6. Ranković V, Kos A, Tomažič S, Milutinović V (2013) Performance of the bitonic mergesort network on a dataflow computer. In: 2013 21st telecommunications forum telfor (TELFOR), Belgrade, 2013, pp 849–852

    Google Scholar 

  7. Kos A, Ranković V, Tomažič S (2015) Sorting networks on maxeler dataflow supercomputing systems. Adv Comput 96:139–186

    Article  Google Scholar 

  8. Milanković I, Mijailović N, Peulić A, Filipović N (2018) Application of data flow engines in biomedical images processing. IPSI BgD Trans Adv Res (TAR), 14(1). ISSN 1820 – 4511

    Google Scholar 

  9. Kotlar M, Milutinović V (2017) Implementing neural networks using the dataflow paradigm. IPSI BgD Trans Adv Res (TAR) 13(1). ISSN 1820 – 4511

    Google Scholar 

  10. Reese L (2018) Comparing hardware for artificial intelligence: FPGAs vs. GPUs vs. ASICs | embedded Intel® Solutions, Eecatalog.com, 2018. Available http://eecatalog.com/intel/2018/07/24/comparing-hardware-for-artificial-intelligence-fpgas-vs-gpus-vs-asics/. Accessed 1 August 2018 (Online)

  11. Amara A, Amiel F, Ea T (2006) FPGA vs. ASIC for low power applications. Microelectron J 37:669–677

    Article  Google Scholar 

  12. Meden R (2017) Maxeler bitcoin miner [source code]. https://github.com/medenko/Maxeler-Bitcoin-Miner

  13. Developer Guide—Bitcoin (2009) Available https://bitcoin.org/en/developer-guide. Accessed 1 July 2017 (Online)

  14. Hash Rate—Blockchain. Available https://blockchain.info/en/charts/hash-rate?timespan=2years. Accessed 1 July 2017 (Online)

  15. Difficulty—Blockchain. Available https://blockchain.info/en/charts/difficulty?timespan=2years. Accessed 1 July 2017 (Online)

  16. Bitcoin Hashrate Distribution—Blockchain.info. Available https://blockchain.info/en/pools. Accessed 1 July 2017 (Online)

  17. Bitmain Antminer S7 Review: Is it Profitable to Buy? (Probably Not). Available https://www.buybitcoinworldwide.com/mining/hardware/antminer-s7/. Accessed 1 July 2017 (Online)

  18. Spondoolies-Tech SP20 Jackson Review: Is it Profitable to Buy? Available https://www.buybitcoinworldwide.com/mining/hardware/spondoolies-sp20/. Accessed 1 July 2017 (Online)

  19. Bitcoin Mining Calculator—BTCServ. Btcserv.net. Available https://btcserv.net/bitcoin-mining-calculator. Accessed 4 Nov 2016 (Online)

  20. Milenković A, Milutinović V (2000) Cache injection: a novel technique for tolerating memory latency in bus-based SMPs. In: European conference on parallel processing. Springer, Berlin, pp. 558–566

    Chapter  Google Scholar 

  21. Furht B, Milutinović V (1987) A survey of microprocessor architectures for memory management. Computer 20. Kovačević M, Diligenti M, Gori M, Milutinović V (2004) Visual adjacency multigraphs-a novel approach for a web page classification. In: Proceedings of SAWM04 workshop

    Google Scholar 

  22. Tomašević M, Milutinović V (1994) Hardware approaches to cache coherence in shared-memory multiprocessors. IEEE Micro 14:61–66

    Article  Google Scholar 

  23. Grujić A, Tomašević M, Milutinović V (1996) A simulation study of hardware-oriented DSM approaches. IEEE Parallel Distrib Technol Syst Appl 4:74–83

    Article  Google Scholar 

  24. Tomašević M, Milutinović V (1992) A simulation study of snoopy cache coherence protocols. In: System sciences, proceedings of the twenty-fifth Hawaii international conference, Hawaii, vol 1, pp 427–436

    Google Scholar 

  25. Tartalja I, Milutinović V (1997) The cache coherence problem in shared-memory multiprocessors: software solutions. IEEE Computer Society Press

    Google Scholar 

  26. Milutinović V (1997) Caching in distributed systems. IEEE Concurr 8:14–15

    Article  Google Scholar 

  27. Milutinović V, Stenstrom P (1999) Special issue on distributed shared memory systems. Proc IEEE 87:399–404

    Article  Google Scholar 

  28. Maxeler Technologies (2015) Multiscale dataflow programming

    Google Scholar 

  29. Milutinović V, Furht B, Obradović Z, Korolija N (2016) Advances in high performance computing and related issues. In: Mathematical problems in engineering

    Google Scholar 

  30. Korolija N, Popović J, Cvetanović M, Bojović M (2017) Dataflow-based parallelization of control-flow algorithms. In: Advances in computers, vol 104. Elsevier, pp 73–124

    Google Scholar 

  31. Trifunović N, Milutinović V, Salom J, Kos A (2015) Paradigm shift in big data supercomputing: dataflow vs. controlflow. J Big Data 2:4

    Google Scholar 

  32. Kos A, Tomažič S, Salom J, Trifunović N, Valero M, Milutinović V (2015) New benchmarking methodology and programming model for big data processing. Int J Distrib Sens Netw 11

    Article  Google Scholar 

  33. Milutinović V, Salom J, Veljović D, Korolija N, Marković D, Petrović L (2017) Transforming applications from the control flow to the dataflow paradigm. In: DataFlow supercomputing essentials. Springer, Cham, pp 107–129

    Chapter  Google Scholar 

  34. Milutinović V, Salom J, Veljović D, Korolija N, Marković D, Petrović L (2017) Discrepancy reduction between the topology of dataflow graph and the topology of FPGA structure. In: DataFlow supercomputing essentials. Springer, Cham, pp 19–66

    Chapter  Google Scholar 

  35. Milutinović V (1989) Mapping of neural networks on the honeycomb architecture. Proc IEEE 77:1875–1878

    Article  Google Scholar 

  36. Descriptions of SHA-256, SHA-384, and SHA-512. Available http://www.iwar.org.uk/comsec/resources/cipher/sha256-384-512.pdf. Accessed 1 July 2017 (Online)

  37. Marek Palatinus (2016) Stratum Mining Proxy [Source Code]. https://github.com/slush0/stratum-mining-proxy

  38. Meden R (2017) Mining bitcoins using maxeler data flow computer. M.S. thesis, Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia

    Google Scholar 

  39. p2pool Nodes. Poolnode.info. Available http://poolnode.info/. Accessed 4 Nov 2016 (Online)

Download references

Acknowledgements

The authors acknowledge the financial support from the Slovenian Research Agency (research core funding No. P2-0246). Special thanks goes to Belgrade team at Maxeler Technologies for providing us access to Maxeler MAX5C board for testing purposes.

Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, University of Ljubljana, Trzaska cesta 25, 1000, Ljubljana, Slovenia

    Rok Meden & Anton Kos

Authors
  1. Rok Meden
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anton Kos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anton Kos .

Editor information

Editors and Affiliations

  1. Indiana University, Bloomington, IN, USA

    Veljko Milutinovic

  2. School of Electrical Engineering, University of Belgrade, Belgrade, Serbia

    Milos Kotlar

Appendices

Appendix 1: BitcoinMinerCpuCode.c

figure g
figure h
figure i
figure j
figure k
figure l
figure m
figure n
figure o

Appendix 2: BitcoinMinerEngineParameters.maxj

figure p

Appendix 3: BitcoinMinerKernel.maxj

figure q
figure r
figure s
figure t
figure u
figure v

Appendix 4: BitcoinMinerManager.maxj

figure ab
figure w

Appendix 5: SHA256-CPU.c

figure x
figure y
figure z
figure aa

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Meden, R., Kos, A. (2019). Bitcoin Mining Using Maxeler DataFlow Computers. In: Milutinovic, V., Kotlar, M. (eds) Exploring the DataFlow Supercomputing Paradigm. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-13803-5_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-13803-5_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-13802-8

  • Online ISBN: 978-3-030-13803-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation