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An Efficient Code Compression Technique using Application-Aware Bitmask and Dictionary Selection Methods

An Efficient Code Compression Technique using Application-Aware Bitmask and Dictionary Selection Methods. Seok-Won Seong and Prabhat Mishra University of Florida IEEE Transaction on Computer Aided Design of Intigrated Systems April 2008, Vol 27, No. 4. Rahul Sridharan. Agenda. Motivation

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An Efficient Code Compression Technique using Application-Aware Bitmask and Dictionary Selection Methods

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  1. An Efficient Code Compression Technique using Application-Aware Bitmask and Dictionary Selection Methods Seok-Won Seong and Prabhat Mishra University of Florida IEEE Transaction on Computer Aided Design of Intigrated Systems April 2008, Vol 27, No. 4 Rahul Sridharan 1 of 25

  2. Agenda • Motivation • Background • Code compression using Bitmasks • Challenges in Bitmask-based approach • Application-Aware Code Compression • Mask Selection • Bitmask-aware Dictionary Selection • Code Compression Algorithm • Results • Conclusion 2 of 25

  3. Motivation • Bitmask-based code compression • Addresses issue of memory constraints in Embedded Systems improving power and performance • Constraints code size • Application-Aware code compression algorithm • Improve compression efficiency without introducing decompression penalty 3 of 25

  4. Background: Code Compression Static Encoding (Offline) Application Program (Binary) Compression Algorithm Dynamic Decoding (Online) Processor (Fetch and Execute) Compressed Code (Memory) Decompression Engine 4 of 25

  5. Code compression approaches Format for Uncompressed Code Format for Compressed Code Decision (1 Bit) Uncompressed Data (32 Bits) Decision (1 Bit) # of Bit Changes Location (5 Bits) … … Location (5 Bits) Dictionary Index • Dictionary based • Frequency based Dictionary-selection Format for Uncompressed Code (32 Bit Code) Format for Compressed Code Decision (1 Bit) Uncompressed Data (32 Bits) Decision (1 Bit) Dictionary Index • Hamming Distance based • Remembering Mismatches • Bit-mask based 5 of 25

  6. Bitmask Encoding 32-bit instructions Format for uncompressed code Format for compressed code … Mask Type Location Mask Pattern Mask Type Location Mask Pattern Decision (1 Bit) Uncompressed Data (32 Bits) Decision (1 Bit) Number of Masks Dictionary Index Actual mask pattern Type of the mask e.g., 2-bit, 4-bit etc. Location to apply the bitmask 6 of 25

  7. Code Compression with Bitmasks Bit Mask Position Bit Mask Value 0 – Bit Mask Used 1 – No Bit Mask Used 0 – Compressed 1 – Not Compressed Original Program Compressed Program Dictionary 0000 0000 1000 0010 0000 0010 0100 0010 0100 1110 0101 0010 0000 1100 0100 0010 1100 0000 0000 0000 0 1 0 0 0 00 11 1 0 0 11 10 0 0 1 1 0 0 10 11 1 0 0 01 01 1 0 0 10 11 0 0 1 1 0 0 00 11 0 0 1 0 7 of 25

  8. Challenges in Bitmask-based Compression Selection of appropriate mask pattern Larger bitmask generates more matches 4-bit mask can handle up to 16 mismatches 8-bit mask can handle up to 256 mismatches Larger bitmask incurs higher cost 4-bit mask costs 7 bits 8-bit mask costs 10 bits Efficient Dictionary Selection Frequency-based selection not always optimum Need for efficient masking and dictionary selection schemes to improve efficiency 8 of 25

  9. Frequency v/s Spanning based Dictionary Selection Spanning-based DS CR = 87.5% Frequency-based DS CR = 97.5% 9 of 25

  10. Application-Aware Code Compression • Bitmask Selection • Bitmask-Aware Dictionary Selection • Nondeterministic polynomial-time-hard problem • Code Compression Algorithm • Based on the combination of the two approaches 10 of 25

  11. Mask Selection How many bitmask patterns are needed? Which of them are profitable? Fixed and sliding bitmask patterns 11 of 25

  12. Mask Selection Bits needed to indicate particular location Size of mask Type of mask No. of bitmask patterns needed Up to two mask patterns Minimum cost to store three bitmasks is 27-31 bits for a 32-bit vector Not very profitable Which combinations are profitable? Eleven possibilities 1s, 2s, 2f, 3s, 4s, 4f, 5s, 6s, 7s, 8s, 8f Select one/two from eleven possibilities Number of combinations can be further reduced 12 of 25

  13. Comparison of Bitmask Combinations Benchmarks are compiled for TI TMS320C6x (1s, 4f) and (2f, 2s) provide the best compression (2s, 2f) (1s, 4f) (1s, 4f) s 13 of 25

  14. Mask Selection: Observations Factors of 32 (1, 2, 4 and 8) produce better results Since they can be applied cost-effectively on fixed locations 8-bit fixed/sliding is not helpful Probability of more than 4 consecutive changes is low Two smaller masks perform better than a larger one 4-bit sliding does not perform better than 4-bit fixed Two bitmasks provide better results than a single one Choose two from four bitmasks: (1s, 2f, 2s, 4s) 14 of 25

  15. Dictionary Selection Dictionary Selection Dynamic Static Frequency Bit Savings Spanning Select patterns to ensure uniform coverage of all patterns based on hamming distance. Select patterns based on bit savings due to self and mask-matched repetitions Select most frequently occurring binary patterns 15 of 25

  16. BitSavings-based Dictionary Selection 16 of 25

  17. BitSavings-based Dictionary Selection A = 0+10 = 10 B = 7+15 = 22 C = 7+15 = 22 D = 0+5 = 5 E = 0+15 = 15 F = 7+20 = 27 G =14+10 = 24 Node Weight: number of bits saved due to frequency of the pattern Edge Weight: number of bits saved due to use of the bitmask based match Total weight: node weight + all edge weights (connected to the node) B(7) C(7) A(0) 5 10 5 10 D(0) G(14) 5 10 F(7) E(0) 17 of 25

  18. BitSavings-based Dictionary Selection A = 0+10 = 10 B = 7+15 = 22 D = 0+5 = 5 G =14+10 = 24 Node Weight: number of bits saved due to frequency of the pattern Edge Weight: number of bits saved due to use of the bitmask based match Total weight: node weight + all edge weights (connected to the node) B(7) A(0) 5 10 5 D(0) G(14) Continues until the dictionary is full or the graph is empty 18 of 25

  19. Application Aware Code Compression 19 of 25

  20. Experiments Experimental Setup Benchmarks: TI and MediaBench Architectures: Sparc, TI TMS320C6x, MIPS Results BCC: Bitmask-based code compression Customized encodings for different architectures Effects of dictionary size selection Comparison with existing techniques ACC: Application-aware code compression Bitmask selection Dictionary selection 20 Of 25

  21. Compression Ratio for adpcm_en Encoding2 outperforms others • Encoding 1 (one 8-bit mask) • Encoding 2 (two 4-bit masks) • Encoding 3 (4-bit and 8-bit masks) 21 of 25

  22. Comparison with other Techniques Outperforms other dictionary-based techniques by 15% Higher decompression bandwidth than existing compression techniques Bitmask Approach Smaller compression ratio is better 22 of 25

  23. Comparison of Dictionary Selection Methods BitSavings approach outperforms both frequency- and spanning-based techniques 23 of 25

  24. Compression Ratio Comparison BCC: Bitmask-based Code Compression ACC: Application-aware Code Compression BCC generates 15-20% improvement over other techniques ACC outperforms BCC by another 5-10% 24 of 25

  25. Questions ??? 25 of 25

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