### Table 3: Traditional method data

1994

"... In PAGE 16: ...1 Data for the Traditional Approach The iterative, bit-vector method for computing liveness information requires four sets be computed and and stored at each block in the program: the in, out, use, and def sets. In Table3 the number of bits required (in thousands) per set is shown for each program. For the entire Perfect suite, this works out to about 300K 32-bit words of storage required for all four sets.... ..."

Cited by 3

### Table 3: Traditional method data

1994

"... In PAGE 16: ...1 Data for the Traditional Approach The iterative, bit-vector method for computing liveness information requires four sets be computed and and stored at each block in the program: the in, out, use, and def sets. In Table3 the number of bits required (in thousands) per set is shown for each program. For the entire Perfect suite, this works out to about 300K 32-bit words of storage required for all four sets.... ..."

Cited by 3

### Table 1: Hardware-based single and multiple instruction rollback schemes.

1993

"... In PAGE 4: ...Hardware schemes such as reorderbuffers,historybuffers, future files[8],and micro-rollba_k[2]differin where the updated and old values reside,circuit complexity,CPU cycletimes,and rollbackefficiency. Table1 givesa descriptionof varioushardware-ba_ed methods to restorethe generalpurpose registerfilecontentsduring singleor multipleinstructionrollback.In the VAX 8600 and VAX 9000, errorsare detected priorto the completion of a faultyinstruction.... ..."

### Table 1. Comparison of traditional and structural test methods

"... In PAGE 2: ...Table1 compares the traditional approach to test with a structured one. There is a heavy reliance on functional tests for all fault types.... ..."

### Table 1: Performance comparison of traditional and cognitive methods

1994

"... In PAGE 5: ... 4 Conclusion Several cognitive methods have been analysed, tried and compared, for the control of an unstable system. Table1 compares the di#0Berent methods in terms of: Number T C... ..."

Cited by 6

### Table 1: Performance comparison of traditional and cognitive methods

1994

"... In PAGE 5: ...enomes as SA #28see tab. 1#29. Ahybrid algo- rithm with just mutations but no crossover has also been tried, as shown in #0Cgure 4. Table1 compares the di#0Berent methods in terms of: Number T C of iterations needed to reach an error close to the asymptotic error e 1 #28namely #0F M #14 1:5e 1 #29; the asymptotic er- ror e 1 , the size of the learning population #28i.e.... ..."

Cited by 1

### Table 1. Comparison of the proposed method with the traditional approach

### Table 1: Traditional method Vs Online Advertising

### Table 1: Traditional estimates and bounds.

1999

"... In PAGE 11: ...xpression on the items in the set. Let v1; : : : ; vn be a uniform random sample of the multiset fx1; : : : ; xmg. We wish to estimate the aggregate (AVG, SUM, and COUNT) on all m values based on this sample of n values. Table1 summarizes the traditional estimates and the bounds for AVG, SUM and COUNT with no predicates, where p is the desired confidence probability. Shown are upper bounds for t such that Pr(je ? j t) p, where is the precise result to an aggregate, and e is an estimate based on n samples.... In PAGE 11: ... The last column indicates whether or not a bound is guaranteed with probability p or holds with probability p only under large sample assumptions [HHW97, Haa97]. Comparing the bounds in Table1 , we see that among the two bounds using ^ , the Chebychev (estimated ) bound is better than the CLT bound whenever n gt; 1=(z2 p(1?p)). Since n must be sufficiently large for either approximation to hold, the Chebychev bound is better unless the desired error probability is inversely proportional to n.... In PAGE 12: ... We report an estimate and a bound based on the ej. We can apply any of the methods in Table1 to obtain the chunk estimators, ej, and the confidence bounds on the estimators. Since each chunk estimator is based on only a subsample, the confidence in a single chunk estimator is less than if it were based on the entire sample.... In PAGE 13: ... Thus the best choice for k depends on the relationship of and t in Equation 2 as a function of k, and the desired confidence p = 1 ? qk. In the remainder of this section, we highlight our results analyzing and comparing the effects of applying the various methods in Table1 , and determining the optimal number of chunks. Table 2 summarizes our analysis on the use of Chebychev for Equation 2 in conjunction with various values for p, with and without chunking.... In PAGE 14: ... The bounds are shown for Chebychev (known ) . Alternatively, as in Table1 , we can obtain bounds for Chebychev (estimated ) by plugging in ^ for in Table 2, where ^ is computed over all the sample points, not just those in one chunk. We can also obtain bounds for Chebychev (conservative) by plugging in (MAX ? MIN)=2 for .... In PAGE 15: ...s queries without joins (i.e., as single-table queries). There are several popular methods (see Table1 ) for obtaining error bounds for approximate answers to (single-table) aggregation queries. We have presented a detailed analysis that demonstrates the precise trade-offs among these methods, as well as a method based on subsampling which we call chunking .... In PAGE 20: ... Figure 5 plots the error bounds for the PropJoin allocation scheme for a summary size of 2%. It shows the 90% confidence bounds of three of the five techniques in Table1 , namely, Hoeffding, Chebychev (estimated ), and Chebychev (conservative).10 These bounds are compared with bounds based on chunk statistics.... ..."

Cited by 116

### Table 1. Traditional Reconfiguration Time

"... In PAGE 6: ... We also employed a Sun R Ultra 10 with 440MHz Ultra- SPARC processor for our experiments as a modern proces- sor. The reconfiguration time of six image processing algo- rithms are measured once using the traditional FPGA physical reconfiguration and directly mapping the appli- cation onto FPGAs and presented in Table1 . Table 2 rep- resents the reconfiguration time using our MSQR method.... In PAGE 6: ... Table 2 rep- resents the reconfiguration time using our MSQR method. As shown in Table1 , instead of performing the processes of synthesis, placement and routing for FPGA recon- figuration which takes hundreds of seconds, the whole procedure can be accomplished in hundreds of microsec- onds using MSQR method. The results of MSQR are il- lustrated in Table 2.... ..."