  Huffman compression is a statistical, lossless, data compression algorithm
that compresses data by assigning variable length codes to symbols, with the
more frequently appearing symbols given shorter codes than the less. This work
is a modification of the Huffman algorithm which permits uncompressed data to
be decomposed into indepen- dently compressible and decompressible blocks,
allowing for concurrent compression and decompression on multiple processors.
We create implementations of this modified algorithm on a current NVIDIA GPU
using the CUDA API as well as on a current Intel chip and the performance
results are compared, showing favorable GPU performance for nearly all tests.
Lastly, we discuss the necessity for high performance data compression in
today's supercomputing ecosystem.
