1. A Survey of Logic Block Architectures For Digital Signal Processing Applications

2. Presentation Outline Considerations in Logic Block Design  Computation Requirements  Why Inefficiencies? Representative Logic Block Architectures  Proposed  Commercial Conclusions: What is suitable Where?

3. Why DSP???  The Context Representative of computationally intensive class of applications  datapath oriented and arithmetic oriented Increasingly large use of FPGAs for DSP  multimedia signal processing, communications, and much more To study the “issues” in reconfigurable fabric design for compute intensive applications  What is involved in making a fabric to accelerate multimedia reconfigurable computing possible?

4. Elements of a Reconfigurable Architecture Logic Block/Processing Element  Differing Grains Fine>>Coarse>>ALUs Routing Dynamic Reconfiguration

5. So what’s wrong with the typical FPGA? Meant to be general purpose  lower risks Toooo Flexible!  Result: Efficiency Gap Higher Implementation Cost, Larger Delay, Larger Power Consumption than ASICs Performance vs. Flexibility Tradeoff  Postponing Mapping and Silicon Re-use

6. Solution? See how FPGAs are Used? FPGAs are being used for “classes” of applications  Encryption, DSP, Multimedia etc. Here lies the Key  Design FPGAs for a class of applications Application Domain Characterization  Application Domain Tuning

7. Domain Specialization COMPUTATION  defines  ARCHITECTURE Target Application Characteristics known beforehand? Yes 1. Characterize the application domain 2. Determine a balance b/w flexibilty vs efficiency 3. Tune the architecture according

8. Categorizing the “Computation” Control  Random Logic Implementation Datapath  Processing of Multi-bit Data Conflicting Requirements???

9. Datapath Element Requirements Operates on Word Slices or Bit Slices Produces multi-bit outputs Requires many smaller elements to produce each bit output  i.e. multiple small LUTs

10. Control Logic Requirements Produces a single output from many single bit inputs Benefits from large grain LUT as logic levels gets reduced

11. Logic Block Design: Considerations “How much” of “what kinds” of computations to support? Tradeoff: Generality vs Specialization

12. How much of What?  Applications benchmarking

13. So what do we have to support? Datapath functionality, in particular arithmetic, is dominant in DSP. The datapath functions have different bit-widths. DSP designs heavily use multiplexers of various size. Thus, an efficient mapping of multiplexers should be supported. DSP functions do contain random logic. The amount of random logic varies per design. Some DSP designs use wide boolean functions.

14. DSP Building Blocks Some techniques widely used to achieve area- speed efficient DSP implementations Bit Serial Computations  Routing Efficient  Bit Level Pipelining Increases throughput even more Digit Serial Computation  Combining “Area efficiency” of bit-serial and with “Time efficiency” of Bit-parallel

15. Classes of DSP-optimized FPGA Architectures 1. Architectures with Dedicated DSP Logic  Homogeneous  Hetrogeneous  Globally Homogeneous, Locally Heterogenous 2. Architectures of Coarser Granularity 3. With DSP Specific Improvements (e.g. Carry Chains, Input Sharing, CBS)

16. Some Representative Architectures

17. Bit-Serial FPGA with SR LUT Bit-serial paradigm suites the existing FPGA so why not optimize the FPGA for it! Logic block to support efficient implementation of bit-serial data path and bit-level pipelining LUTs can be used for combinational logic as well as for Shift Registers

18. A Bit-Serial Adder A Bit-Serial Adder which processes two bits at a time Interface Block Diagram

19. A Bit-Serial Multiplier Cell

20. The Proposed Bit Serial Logic Block Architecture 4x4-input LUTs and 6 flip-flops. The two multiplexers in front of the LUTs are targeted mainly for carry-save operations which are frequently used in bit- serial computations. There are 18 signal inputs and 6 signal outputs, plus a clock input. Feed-back inputs c2, c3, c4, c5 can be connected to either GND or VDD or to one of the 4 outputs d0, d1, d2, d3. Therefore, each LUT can implement any 4-input functions controlled by inputs a0, a1, a2, a3 or b0, b1, b2, b3. Programmable switches connected to inputs a4 and b4 control the functionality of the four multiplexers at the output of LUTs. As a result, 2 LUTs can implement any 5-input functions. The final outputs d0, d1, d2, d3 can either be the direct outputs from the multiplexers or the outputs from flip-flops. All bit-serial operators use the outputs from flip-flops; therefore the attached programmable switches are actually unnecessary. They are only present in order to implement any other logic functions other than bit-serial datapath circuits. Two flip-flops are added (inputs c0 and c1) to implement shift registers which are frequently used in bit-serial operations.

21. The Modified LUT Implementing a Shift Register

22. Performance Results

23. Digit-Serial Logic Block Architecture Digit–Serial Architectures process one digit (N=4 bits) at a time They offer area efficiency similar to bit- serial architectures and time-efficiency close to bit-parallel architectures N=4 bits can serve as an optimal granularity for processing larger digit sizes (N=8,16 etc)

24. Digit-Serial Building Blocks A Digit-Serial Adder A Digit-Serial Unsigned Multiplier

25. Digit-Serial Building Blocks A Pipelined Digit-Serial Unsigned Multiplier For Y=8 bits

26. Digit-Serial Signed Multiplier Blocks Middle Stages ModuleFirst Stage ModuleLast Stage Module

27. Signed Digit-Serial Multiplier A Digit-Serial Signed Booth’s Pipelined Multiplier with Y=8

28. Proposed Digit-Serial Logic Block

29. Detailed Structure of Digit-Serial Logic Block

30. The Basic Logic Module (LM) The Structure of the LM Table of Functions Implemented

31. Examples of Implementations N=4 Unsigned Multiplier N=4 Signed Multiplier Two N=2 Multipliers Bit-Level Pipelined

32. Area Comparison with Xilinx 4000 Series

33. Mixed-Grain Logic Block Architecture Exploits the adder inverting property Efficiently implements both datapath and random logic in the same logic block design

34. Adder Inverting Property Full Adder and Equations Showing The Inverting Property An optimal structure derived from the property

35. LUT Bits Utilization in Datapath and Logic Modes

36. Structure of a Single Slice

37. Complete Logic Block

38. Modified ALU Like Functionality

39. Comparison Results

40. Comparison Results (Cont…)

41. Comparison Results (cont…)

42. Coarser ALU Like Architectures

43. CHESS Architecture

44. CHESS ALU Based Logic Block

45. Structure of a Switch Box

46. Comparison Results

47. Computation Field Programmable Architecture A Heterogeneous architecture with cluster of datapath logic blocks Separate LUT Based Logic Blocks for supporting random logic mapping Basic Logic Block called a Partial Adder Subtraction Multiplier (PASM) Module

48. PASM Logic Block of CFPA

49. Cluster of PASM Logic Blocks

50. Comparison Results

51. Some Industry Architectures Designs

52. Altera APEX II Logic Element

53. Altera MAX II Logic Element

54. LE Configuration in Arithmetic Mode

55. LE in Random Logic Implementation

56. Altera Stratix Logic Element

57. Altera Stratix II Architecture

58. Stratix II Adaptive Logic Module

59. Stratix II ALM in Arithmetic Mode

60. Various Configurations in an ALM of Stratix II

61. Multiplier Resources in Stratix II

62. Structure of a DSP Block in Stratix II

63. XILINX Virtex II Pro Architecture

64. Basic Logic Element of Virtex II Pro

65. Dedicated Multipliers in Virtex II Pro

66. Processor- Programmable Logic Coupled Architecture

67. PiCoGA Architecture Coupled with a VLIW processor

68. PiCoGA Logic Block

69. Conclusions Traditional general purpose FPGA inefficient for data path mapping Logic blocks with DSP specific enhancements seem a promising solution Coarse Grained Logic can achieve better application mapping for data path but sacrifice flexibility Dedicated Blocks (Multipliers) increase performance but also increases cost significantly

70. Conclusions PDSPs with embedded FPGA can achieve a good balance between performance and power consumption So…Which approach is the best?  No single best exists

71. Suitability of Approaches Highly computationally intensive applications with large amounts of parallelism can use platform FPGAs where often large resources are required and power consumption is not an issue. Here cost/function will be lowest

72. Suitability of Approaches Field Programmable Logic based coprocessors can benefit from coarse grained blocks where most control functions are implemented by the PDSP itself

73. Suitability of Approaches Higher flexibility and lower cost can be achieved with logic blocks with DSP specific enhancements but flexibility to implement control logic in an efficient manner.