Greedy Based Approach for Test Data Compression Using Geometric Shapes
Greedy Based Approach to Test Data Compression using Geometric Shapes
ABSTRACT
Systems-on-a-chip (SOC) are comprised of a collection of pre-designed and preverified cores and user defined logic (UDL). As the complexity of systems-on-a-chip continues to increase, the difficulty and cost of testing such chips is increasing rapidly.
One of the challenges in testing SOC is dealing with the large size of test data that must be stored in the tester and transferred between the tester and the chip. The cost of automatic test equipment (ATE) increases significantly with the increase in their speed, channel capacity and memory. As testers have limited speed, channel bandwidth and memory, the need for test data reduction becomes imperative.
This project deals with lossless compression of test vectors on the basis of geometric shapes. It consists of two phases: i) Encoding or Compression and ii) Decoding or Decompression. During the compression phase we exploit reordering of test vectors to minimize the number of shapes needed to encode the test data. The test set is partitioned into blocks and then each block is encoded separately. The encoder has the choice of encoding either the 0‘s or the 1‘s in a block. In addition, it encodes a block that contains only 0‘s (or 1‘s) and x‘s with only 3 bits. Furthermore, if the cost of encoding a block using geometric shapes is higher than the original cost of the block, the block is stored as is without encoding. We have created a new greedy based algorithm to find the shapes present in a block in minimal time. This algorithm after analysis seems to be at least 50% more efficient than the algorithm proposed by the author of the original paper which has been implemented in our program. During the decoding phase the data is read from the compressed file and decoded based on the format in which it was encoded. These phases have been implemented using software. The application gives a good compression ratio of nearly 50% under average
ABSTRACT
Systems-on-a-chip (SOC) are comprised of a collection of pre-designed and preverified cores and user defined logic (UDL). As the complexity of systems-on-a-chip continues to increase, the difficulty and cost of testing such chips is increasing rapidly.
One of the challenges in testing SOC is dealing with the large size of test data that must be stored in the tester and transferred between the tester and the chip. The cost of automatic test equipment (ATE) increases significantly with the increase in their speed, channel capacity and memory. As testers have limited speed, channel bandwidth and memory, the need for test data reduction becomes imperative.
This project deals with lossless compression of test vectors on the basis of geometric shapes. It consists of two phases: i) Encoding or Compression and ii) Decoding or Decompression. During the compression phase we exploit reordering of test vectors to minimize the number of shapes needed to encode the test data. The test set is partitioned into blocks and then each block is encoded separately. The encoder has the choice of encoding either the 0‘s or the 1‘s in a block. In addition, it encodes a block that contains only 0‘s (or 1‘s) and x‘s with only 3 bits. Furthermore, if the cost of encoding a block using geometric shapes is higher than the original cost of the block, the block is stored as is without encoding. We have created a new greedy based algorithm to find the shapes present in a block in minimal time. This algorithm after analysis seems to be at least 50% more efficient than the algorithm proposed by the author of the original paper which has been implemented in our program. During the decoding phase the data is read from the compressed file and decoded based on the format in which it was encoded. These phases have been implemented using software. The application gives a good compression ratio of nearly 50% under average
References: Aiman El-Maleh , Saif al Zahir , Esam Khan,‖Test data compression based on geometric shapes‖, Computers and Electrical Engineering,vol 37,2011,pp 376–391 [1] [2] Thomas H. Cormen,Charles E. Leiserson,Ronald L. Rivest, Clifford Stein,‖Introduction to Algorithms‖,PHI. Department of Computer Science and Engg, TKMCE Page 100