No abstract

Excessive switching activity during scan testing can cause average power dissipation and peak power during test to be much higher than during normal operation. This can cause problems both with heat dissipation and with current spikes. Compacting scan vectors greatly increases the power dissipation for the vectors (generally the power becomes several times greater). The compacted scan vectors often can exceed the power constraints and hence cannot be used. It is shown here that by carefully selecting the order in which pairs of test cubes are merged during static compaction, both average power and peak power for the final test set can be greatly reduced. A static compaction procedure is presented that can be used to find a minimal set of scan vectors that satisfies constraints on both average power and peak power. The proposed approach is simple yet effective and can be easily implemented in the conventional test vector generation flow used in industry today. 0-7695-0613-5/00 $10.00 ã 2000 I

Abstract-This paper presents a compression/decompression scheme based on selective Huffman coding for reducing the amount of test data that must be stored on a tester and transferred to each core in a system-on-a-chip (SOC) during manufacturing test. The test data bandwidth between the tester and the SOC is a bottleneck that can result in long test times when testing complex SOCs that contain many cores. In the proposed scheme, the test vectors for the SOC are stored in compressed form in the tester memory and transferred to the chip where they are decompressed and applied to the cores. A small amount of on-chip circuitry is used to decompress the test vectors. Given the set of test vectors for a core, a modified Huffman code is carefully selected so that it satisfies certain properties. These properties guarantee that the codewords can be decoded by a simple pipelined decoder (placed at the serial input of the core's scan chain) that requires very small area. Results indicate that the proposed scheme can provide test data compression nearly equal to that of an optimum Huffman code with much less area overhead for the decoder.

No abstract

No abstract