Aim

The aim of this course is to introduce you to the basics of Computing in Space.

Learning Outcomes/Objectives

After completing this course you will understand:
• the fundamental methods and techniques
• the multiple dimensions of computing
• the main differences with temporal computing;
will know how to address design implications:
• at application and algorithmic levels
• by solving system-level bottlenecks
• by customizing data choreography
• by using arithmetic level optimizations;
and will become proficient in:
• splitting optimally applications into controlflow and dataflow
• implementing and debugging high-performance parallel algorithms in space
• reasoning about spatial complexity of algorithms, arithmetic and data moves
• computational area and bandwidth trade-offs to improve performance
• achieving maximal performance on a specific spatial computer implementation.

Description and Assessment

The course covers the whole range of issues related to programming and optimization of Spatial Computing Systems. The written examination (open book) in w11 contributes 80% to the overall mark while the individula project contributes 20%. Unassessed practice test for formative assessment only are available here (TBD).

Teaching Assistant

(TBD)

Prerequisites

Java, Computer Architecture I, Logic Design, Algorithms and Data Structures

Syllabus

• Computing in Space Basic Concepts
• Converting Temporal Code to Graphs
• OpenSPL
• DataFlow Engines (DFEs)
• Basic programming of DFEs
• Advanced programming of DFEs
• Dynamic techniques and multiple kernels management
• Application Case Studies
• Achieving Performance
• Numerics in Space
• The Spatial System Perspective
• Complexity of Computing in Space
• Spatial Systems Debugging
• Verifying your Results
• Performance Modelling
• Economics of Computing in Space

Reading List

• Validity of the single processor approach to achieving large scale computing capabilities, Gene M Amdahl, AFIPS spring joint computer conference, IBM Sunnyvale, California, 1967.
• Some Computer Organizations and Their Effectiveness, Michael J Flynn, IEEE Trans. Computers, CÐ21 (9): 948Ð960, Sept 1972.
• Computer Architecture: Pipelined And Parallel Processor Design, (Chapters 1-7) Michael J Flynn, May 1995.
• iWarp: An integrated solution to high-speed parallel computing, S. Borkar, R. Cohn, G. Cox, S. Gleason, T. Gross, H. T. Kung, M. Lam, B. Moore, C. Peterson, J. Pieper, L. Rankin, P. S. Tseng, J. Sutton, J. Urbanski, and J. Webb. In Proceedings of IEEE/ACM SC '88, pages 330-339, Orlando, Florida, November 1988.
• Decoupled access/execute computer architectures, J. E. Smith, Computer Systems, ACM Transactions on; Volume 2, Issue 4, pp 289-308, November 1984.
• OpenSPL Specification, v1.0, http://www.openspl.org
• Sparse Coefficient polynomial approximations for hardware implementations, N. Brisebarre, J. M. Muller and A. Tisserand, In Proc. of 38th Asilomar Conference on Signals, Systems and Computers, pp. 532-535, California, USA, 2004.
• Moving from Petaflops to Petadata, Communications of the ACM, Vol. 56 No. 5, May 2013.
• Finding the Right Level of Abstraction for Minimizing Operational Expenditure, Workshop on High Performance Computational Finance at SC11, November 2011.
• Rapid Computation of Value and Risk for Derivatives Portfolios, Concurrency and Computation: Practice and Experience, Special Issue Paper, July 2011.
• Beyond Traditional Microprocessors for Geoscience High-Performance Computing Applications, IEEE Micro, vol. 31, no. 2, March/April 2011.

Lecture Schedule / Notes (Autumn 2014)

Week	Lectures	Project	Extras
2	Introduction   1 - Computing in Space Basic Concepts   2 - Converting Temporal Code to Graphs	None	None
3	3 - OpenSPL   4 - DataFlow Engines (DFEs)	None	None
4	5 - Basic programming of DFEs   6 - Advanced programming of DFEs	Project: Using a DFE	None
5	7 - Counters, Offsets and DFE mapping   8 - Programming DFEs (Loops)	None
6	9 - Programming DFEs (Loops II) (PDF) (PPSX)   10 - Correlation Example (PDF) (PPSX)	Correlation Lab Excercise (Topic10/p14)
7	11 - Numerics in Space I   12 - Numerics in Space II	Correlation
8	13 - 3D Space (Part 1)   14 - 3D Space (Part 2)	Correlation
9	15 - Porting CPU Software to DFEs   16 - Estimating DFE Performance	Correlation

Web based Design Environment (WebIDE)

You can find WebIDE here. Please note that you can use the departmental computers for the simulation. Installation on your notebook will not work due to various licensing restrictions of the different tools involved.

Other useful information

Self-assessment using unassessed exercises (with model answers).

There are no office hours. Please send us an e-mail in case you have a question.

Page maintained by: Georgi Gaydadjiev
Last updated: 24 November 2014