Off-chip buses consume a huge fraction (20%-40%) of the system power. Hence, techniques
such as increasing bus widths, transition encoding etc. have been used for
power reduction on off-chip data buses. Since capacitances at the I/O pads and interwire
capacitances contribute significantly to increase in power, encoding/decoding
schemes have been developed to reduce switching activity of the off-chip bus lines,
thus reducing power. Frequent-Value Encoding(FVE) [1], Frequent Value Encoding
with Xor (FVExor) [1] and VALVE [2] are some of the better known encoding schemes
but they still have scope for improvement.
This thesis addresses the problem of power reduction in off-chip data buses by
encoding variable number (1 to 4) of fixed-size (32-bit) data values (variable length
patterns) which exhibit temporal locality. This characteristic enables us to cache
these patterns using 64-entry CAM at the encoder and 64-entry SRAM at the decoder.
Whenever a pattern match occurs a 2-bit code indicating the index of the match is
sent. If a variable length pattern match occurs then the code and unmatched portion
of data is sent.
We implemented our scheme, Variable Length Pattern Coding (VLPC) for various
integer and floating point benchmarks and have seen 6% to 49% encodable patterns
in these benchmarks. Based on the experiments on simplescalar and our analysis
in MATLAB, we obtained 4.88% to 40.11% reduction in transition activity for SPEC2000 benchmarks such as crafty, swim, mcf, applu, ammp etc. over unencoded
data. This is 0.3% to 38.9% higher than that obtained using FVE, FVExor [1] and
VALVE [2] encoding schemes. Finally, we have designed a low-power custom CAM
and SRAM using 45nm BSIM4 technology models which has been used to verify lower
latency of data matching and storing.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2667 |
| Date | 15 May 2009 |
| Creators | Venkitasubramanian Iyer, Jayakrishnan |
| Contributors | Kim, Eun Jung |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | electronic, application/pdf, born digital |
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