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art placement of compressed bitstreams to enable fast decompression of variable-length coding (VLC)[1]-[3]. Next, it selects bitmask-based compression parameters suitable for bitstream compression. Finally, it efficiently combines run length encoding (RLC) [4] and bitmask-based compression to obtain better compression and faster decompression.

DECODE-AWARE压缩比特流-2. DECODE-AWARE BITSTREAM COMPRESSION

Fig.1.shows our decode-aware bitstreamcompression framework.Onthe compression side, FPGA configuration bitstream is analyzed for selection of profitable dictionary entries and bitmask patterns. The compressed bitstream is then generated using bitmask-based compression [5] and run length encoding (RLE). Next, our decode-aware placement algorithm is employed to place the compressed bitstream in the memory for efficient decompression. During run-time, the compressed bitstream is transmitted from the memory to the decompression engine, and the original configuration bitstream is produced by decompression.

Algorithm 1 outlines four important steps in our decode-aware compression framework (shown in Fig. 1):

1) bitmask selection; 2) dictionary selection;3) integrated

RLE compression; and 4) decode-aware placement. The input bitstream is first divided into a sequence of symbols with length of . Then bitmask patterns and dictionary entries used for bitmask-based compression are selected. Next, the symbol sequence is compressed using bitmask and RLE. We use the same algorithm [5] to perform the bitmask-based compression. The RLE Compression in our algorithm is also discussed in later chapter. Finally, we place the compressed bitstream into a decode friendly layout within the memory using placement algorithm.

压缩字典-3.DICTIONARY BASED COMPRESSION

This section describes the existing dictionary-based approaches and analyzes their limitations. First, we describe the standard dictionary-based approach [5]. Next, we describe the existing techniques that improve the standard approach by considering mismatches (hamming distance). Finally, we perform a detailed cost-benefit analysis of the recent approaches in terms of how many repeating patterns they can generate from the mismatches. This analysis forms the basis of our technique to maximize the repeating patterns using bitmasks.

Dictionary-Based Approach:

Dictionary-based code-compression techniques provide compression efficiency as well as fast decompression mechanism. The basic idea is to take advantage of commonly occurring instruction sequences by using a dictionary. The repeating occurrences are replaced with a code word that points to the index of the dictionary that contains the pattern. The compressed program consists of both code words and uncompressed instructions. Fig. 2 shows an example of dictionary based code compression using a simple program binary [6]. The binary consists of ten 8-b patterns, i.e., a total of 80 b. The dictionary has two 8-b entries. The compressed program requires 62 b, and the dictionary requires 16 b. In this case, the CR is 97.5%. This example shows a variable-length encoding. As a result, there are several factors that may need to be included in the computation of the CR, such as byte alignments for branch targets and the address-mapping table.

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