Lecture 16 RC Architecture Types & FPGA Interns Lecturer.pptx
- 1. Lecture 16 RC Architecture Types & FPGA Interns Lecturer: Simon Winberg Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
- 2. Reminders & YODA milestone dates Marking process RC Architecture overview & main types Recap of FPGAs Evaluating Performance of Combinational Logic / FPGA design (slides 22)
- 3. Indicate your YODA team in the Wiki. Add a blog entry to describe your topic 29 Apr – Blog about your product 15 May – Design Review 18-20 May – Demos 22 May final report & code (although no late penalty if submitted before 25 May 8am) See “EEE4084F YODA Mark Allocation Schema.pptx” for process of allocating marks for mark categories
- 4. Assignment work is marked in relation to Correctness Completion Structure, effectiveness of wording & layout Adequate amount of detail/results shown & effectively dealing with the details Indication of student’s understanding and engagement with the discipline Clarity of explanations/motivation of results Professionalism and overall quality
- 5. RC Architectures Overview Reconfigurable Computing
- 6. A determining factor is ability to change hardware datapaths and control flows by software control This change could be either a post-process / compile time or dynamically during runtime (doesn’t have to be both) processing elements Datapath While the trivial case (a computer with one changeable datapath could be argued as being reconfigurable) it is usually assumed the computer system concerned has many changeable datapaths.
- 7. Currently there are two basic forms: Microprocessor-based RC FPGA-based RC Microprocessor-based RC: • A few platform configurability features added to a microprocessor system (e.g., a multi-processor motherboard that can reroute the hardware links between processors) • Besides that we’ve already seen it all in the microprocessor parallelism in part of the course
- 8. Microprocessor based RC Multi-core processors dynamically joined to create a larger/smaller parallel system when needed Assumed to be a single computer platform as apposed to a cluster of computers Needs to support software-controlled dynamic reconfiguration (see previous slide) Tends to become: Hardware essentially changeable in big blocks (“macro-level reconfiguration” - whole processors at a time)
- 9. FPGA based Generally much smaller level of interconnects (more at the “micro-level reconfiguration”) Processors that connect to FPGA(s)
- 10. Generally, these systems follow a processors + coprocessors arrangement CPU connectors to reprogrammable hardware (usually FPGAs) The CPU itself may be entirely in an FPGA The lower-level architecture is more involved… CPU FPGA-based Accelerator card … high-speed bus CPU … FPGA-based Accelerator card topic of Seminar #8 (‘Interconnection Fabrics’) and further discussed in later lectures.
- 11. FPGA Interns EEE4084F Skip to slide 22; already covered in text book but scan through these slides to ensure you are well versed in these issues.
- 12. FPGA internal structure Programmable interconnect Programmable logic blocks Image adapted from Maxfield (2004) Programmable logic element (PLE) (or FPLE*) * FPLE = Field Programmable Logic Element Note: one programmable logic block (PLB) may contain a complex arrangement of programmable logic elements (PLE). The size of a FPGA or programmable logic device (PLD) is measured in the number of LEs (i.e., Logic Elements) that it has.
- 13. You already know all your logic primitives… The primitive logic gates AND, OR, NOR, NOT, NOR, NAND, XOR AND3, OR4, etc (for multiple inputs). Pins / sources / terminators Ground, VCC Input, output Storage elements JK Flip Flops Latches Others items: delay, mux OR Input Pin Output Pin Altera Quartus II representations
- 14. A simple but powerful approach to FPGA design is to use lookup tables for the PLBs. These are usually implemented as a combination of a multiplexer and memory (even just using NOR gates) Essentially, this approach is building complex circuits using truth tables (where each LUT enumerates a truth table) The usual strategy for implementing PLBs examples follows…
- 15. Simple 3-LUT implementation for a PLB 0 1 1 0 1 0 0 1 8-bit static memory 3 3-bit input bus 1-bit output 000 001 010 011 100 101 110 111 Any guesses as to what logic circuit this LUT implements? input values
- 16. Simple 3-LUT implementation for a PLB input lines It’s an XOR of the 3 input lines!!! output 0 1 1 0 1 0 0 1 000 001 010 011 100 101 110 111 in out
- 17. Mainstream* Programmable Logic Block (PLB) k-input LUT DFF clock … k inputs output config_sync Configure synchronous or asynchronous response (i.e. a line from another big LUT). 0 1 Image adapted from Maxfield (2004) Another example for implementing an alternate logic function. * Used by manufacturers like Xilinx
- 18. Logic block clusters (LBCs) and Configurable logic blocks (CLBs) • Assume a k-input LUT for each logic block (LB) • Assume N x LBs per logic cluster • BLEs in each logic clusters are fully connected or mostly connected Diagram adapted from Sherief Reda (2007), EN2911X Lecture 2 Fall07, Brown University The diagram shows the same input lines (I) are sent to each LB, in addition to each of the N LBs’ output lines. Each LB operates on 4 input lines at a time, and a MUX is used to decide which input to sample. The MUXs may be configured from a separate LUT, or could be controlled by the LB it is connected to. LB LB … N x LBs
- 19. “Every slice contains four logic-function generators (or LUTs), eight storage elements, wide- function multiplexers, and carry logic. These elements are used by all slices to provide logic, arithmetic, and ROM functions. In addition to this, some slices support two additional functions: storing data using distributed RAM and shifting data with 32-bit registers. Slices that support these additional functions are called SLICEM; others are called SLICEL. SLICEM represents a superset of elements and connections found in all slices. Each CLB can contain zero or one SLICEM. Every other CLB column contains a SLICEMs. In addition, the two CLB columns to the left of the DSP48E columns both contain a SLICEL and a SLICEM.” Source: http://www.xilinx.com/support/documentation/user_guides/ug364.pdf pg 8
- 20. SLICEM slices support additional functions; they are a superset of SLICELs; i.e. the have all the standard LEs plus some additions. Source: http://www.xilinx.com/support/documentation/user_guides/ug364.pdf pg 9
- 21. SLICEL slices contain the standard set of LEs for the particular FPGA concerned. As the diagram shows, it looks a little less complicated than the design of a SLICEM. Source: http://www.xilinx.com/support/documentation/user_guides/ug364.pdf pg 10
- 22. Evaluating Performance Evaluating synthesis (simplified) of an FPGA design
- 23. HDL to FPGA execution & LE cost Map ‘AND(e,f,g)’ to LB1 In order to implement a HDL design, the design need to be decomposed and mapped to the physical LBs on the FPGA and the interconnects need to be appropriately configured. Example: x = AND(e,f,g) y = AND(b,NAND(NAND(b,c),d)) out = NAND((NAND(x,y),NAND(a,y)) out x y Map ‘NAND((NAND(x,y),NAND(a,y))’ to LB2 Map ‘AND(b,NAND(NAND(b,c),d)) ’ to LB3 Costing: 3 LBs, 8 LEs (assuming LBs have LEs that are AND or NAND gates)
- 24. The previous slide didn’t show whether the connections were synchronized (i.e., a shared clock) or asynchronous –since they are all logic gates and no clocks show it’s probably asynchronous Determining the timing constrains for synchronous configurations are generally easier, because everything is related to the clock speed. Still, you need to keep in mind cascading calculations. For asynchronous use, the implementation could run faster, but can also become a more complicated design, and be more difficult to work out the timing…
- 25. Keep in mind that the propagation delays for the various gates / LUTs may be different – for example, in the previous example, let’s assume each AND may take 6ns to stabilise, and the NANDS 10ns. So time to compute out is = MAX OF (time to compute x, time to compute y) + 2x10ns = (2x10ns+6ns) + 20ns = 46ns = pretty fast!! Or is it?? Compared to a 1GHz CPU using just registers (and no mem access)? Try this calculation for yourself ... (assume each instruction takes on avg. 3 clocks due to pipeline, data dependencies, etc, as worst case performance on a RISC processor)
- 26. CPU running at 1GHz each clock 1ns period Assume each instruction takes ~ 5 clocks each due to pipeline etc CODE: int doit ( unsigned a, b, c, d, e, f, g ) { unsigned x = AND(e,f,g); unsigned y = AND(b,NAND(NAND(b,c),d)) out = NAND((NAND(x,y),NAND(a,y)) return out; } unsigned t1 = AND(e,f); 1 instruction, i.e. AND t1,e,f unsigned x = AND(t1,g); unsigned t1 = NAND(b,c) unsigned t2 = NAND(t1,d) unsigned y = AND(b,t2) t1 = NAND(x,y) t2 = NAND(a,y) out = NAND(t1,t2) in all 8 instructions 8 x 3 clocks ea. = 24 ns (assuming all registers pre-loaded) A speed-up of 1.92 over the FPGA case But some of these Can’t be done as just 1 RISC instruction.
- 27. RC architecture case studies IBM Blade & the cell processor Some large-scale RC systems Amdahl’s Law reviewed and critiqued
- 28. Image sources: FYI Stamp – Wikipedia open commons Reminder stamp – Open Clipart www.openclipart.org (public domain) Xilinx FPGA related images & schematics – from Xilinx datasheets or their website Disclaimers and copyright/licensing details I have tried to follow the correct practices concerning copyright and licensing of material, particularly image sources that have been used in this presentation. I have put much effort into trying to make this material open access so that it can be of benefit to others in their teaching and learning practice. Any mistakes or omissions with regards to these issues I will correct when notified. To the best of my understanding the material in these slides can be shared according to the Creative Commons “Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)” license, and that is why I selected that license to apply to this presentation (it’s not because I particulate want my slides referenced but more to acknowledge the sources and generosity of others who have provided free material such as the images I have used).