"... In PAGE 11: ...2. Table7 presents a summary of the above allocator algorithms, along with their speed, scalability, false sharing and blowup char- acteristics. As can be seen from the table, the algorithms closest to Hoard are Vee and Hsu, DYNIX, and LKmalloc.... ..."

"... In PAGE 3: ... Un- like Hoard, both of these allocators passively induce false sharing by allowing pieces of the same cache line to be recycled. Table1 presents a summary of allocator algorithms, along with their speed, scalability, false sharing and blowup characteristics. Hoard is the only one that solves all four problems.... ..."

"... In PAGE 4: ...ssumed to be modulo N, e.g., queue N + 1 actually refers to queue 1. The number of jobs served during a visit to a queue is determined by either exhaustive or gated service, as we described in Section 1. Then, during the visit to each queue, we allow jobs to be scheduled for service according to a variety of scheduling policies, summarized in Table1 . However, we limit the discussion to work-conserving disciplines, i.... ..."

"... In PAGE 15: .../(K!20)~(0.6*K)~(0.4*2O-Kt9+111) The required probability can also be approximated by using the normal distribution, as shown later in this paper. Continuous random variables Summarized in Table2 are facts about some of the most common uniform theoretical continuous random variables that are used in com- distribution puter system design and analysis. If X has a uniform distribution its values are restricted to a finite interval, and the probability that the value of X falls in any particular subinterval is the ratio of the length of that subinterval to the length of the whole inter- val.... In PAGE 15: ...5. Also,by Table2 ,E[X]=15andVar[X]=102+12=8.33.... In PAGE 18: ... = 1/0.05. Hence the probability that X does not exceed 75 milliseconds is given by F,(0.075) which by Table2 has the value Similarly, the probability that the value of X does not exceed 50 milliseconds is 4 5.i 1 - e-5 x T= 0.... ..."

"... In PAGE 8: ... The two rightmost columns show examples of the warpings returned by both algorithms. Table1 contains a numerical comparison. 4.... ..."

"... In PAGE 24: ... The primary motivation here is to increase reliability rather than to make model construction easier. We have illustrated this synergy by describing three applications in diagnostics, control, and prediction, as summarized in Table3 . These studies stem from real- world, high-impact business problems, such as gas turbine service and diagnosis, freight train control, and residential property valuation, respectively, and use a number of different means from the toolbox of soft computing.... ..."

"... In PAGE 39: ... 39 Table1 0: Total signs available for comparison (short wordlist) Rusia #1 67 Rusia #2 73 7 Ukraine 73 77 83 Moldova 73 78 83 83 Estonia #1 72 77 82 82 83 Estonia #2 73 78 83 83 84 83 Latvia 73 78 83 83 84 83 84 Poland #1 73 78 83 83 84 83 84 84 Poland #2 71 77 81 81 82 81 82 82 82 Slovakia #1 68 74 78 78 79 78 79 79 79 78 Slovakia #2 71 77 81 81 82 81 82 82 82 80 79 Slovakia #3 70 75 79 79 80 80 80 80 80 80 76 78 Czech Republic #1 73 78 83 83 84 83 84 84 84 82 79 82 80 Czech Republic #2 73 78 83 83 84 83 84 84 84 82 79 82 80 84 Romania 73 78 83 83 84 83 84 84 84 82 79 82 80 84 84 Hungary 72 77 82 82 83 82 83 83 83 81 78 81 79 83 83 83 Bulgaria 70 76 80 80 81 80 81 81 81 79 77 80 77 81 81 81 80 Croatia 73 78 83 83 84 83 84 84 84 82 79 82 80 84 84 84 83 81 ASL #1 72 77 82 82 83 82 83 83 83 81 78 81 79 83 83 83 82 80 83 ASL #2 72 77 82 82 83 82 83 83 83 81 78 81 79 83 83 83 82 80 83 83 ASL #3 64 70 74 74 75 74 75 75 75 74 72 74 72 75 75 75 74 73 75 74 74... In PAGE 40: ... 40 Table1 1: Percentage of similar signs (complete wordlist) Rusia #1 72 Rusia #2 74 72 Ukraine 73 67 74 Moldova 43 41 42 42 Estonia #1 Estonia #2 Latvia Poland #1 Poland #2 37 36 35 35 40 Slovakia #1 39 37 38 37 36 72 Slovakia #2 40 40 41 39 40 75 89 Slovakia #3 37 35 38 41 36 50 52 53 Czech Republic #1 34 33 34 36 34 48 50 52 84 Czech Republic #2 41 41 41 40 38 40 45 48 40 39 Romania 38 36 37 38 38 46 51 53 49 50 48 Hungary 46 46 44 43 43 46 48 50 44 41 46 39 Bulgaria Croatia 41 39 38 43 36 34 36 39 41 39 34 40 41 ASL #1 39 36 37 42 34 33 35 38 42 39 33 39 39 92 ASL #2 39 37 36 42 34 33 34 38 41 39 31 38 38 94 92 ASL #3 36 33 34 41 32 30 32 35 43 39 31 37 36 89 91 89... In PAGE 41: ... 41 Table1 2: Percentage of similar signs (short wordlist) Rusia #1 76 Rusia #2 71 65 Ukraine 73 68 64 Moldova 49 49 42 47 Estonia #1 50 45 51 49 76 Estonia #2 56 53 54 58 48 54 Latvia 48 40 39 45 36 40 44 Poland #1 44 44 36 43 36 41 48 73 Poland #2 48 52 44 44 48 44 45 45 51 Slovakia #1 46 46 44 44 43 47 46 49 49 72 Slovakia #2 51 53 47 46 52 52 55 51 55 80 85 Slovakia #3 47 47 47 54 43 46 53 60 60 58 66 64 Czech Republic #1 45 46 41 47 42 45 46 60 60 54 62 62 88 Czech Republic #2 48 50 41 47 45 47 51 48 52 49 54 57 55 51 Romania 52 50 46 48 46 49 50 52 54 52 58 57 64 60 56 Hungary 56 61 48 51 54 49 51 51 49 59 58 63 59 55 59 52 Bulgaria 41 46 34 35 37 36 44 44 44 48 51 53 51 48 56 51 51 Croatia 48 45 39 46 46 41 46 39 38 46 48 52 48 44 46 48 49 41 ASL #1 50 44 40 46 42 41 49 40 40 46 49 49 49 46 46 47 48 40 92 ASL #2 42 39 33 41 42 37 41 39 37 42 42 46 42 41 41 42 43 36 90 86 ASL #3 47 41 36 45 43 42 45 44 40 42 47 46 56 49 44 44 46 40 88 89 85... ..."

"... In PAGE 11: ...2. Table7 presents a summary of the above allocator algorithms, along with their speed, scalability, false sharing and blowup char- acteristics. As can be seen from the table, the algorithms closest to Hoard are Vee and Hsu, DYNIX, and LKmalloc.... ..."

"... In PAGE 11: ...2. Table7 presents a summary of the above allocator algorithms, along with their speed, scalability, false sharing and blowup char- acteristics. As can be seen from the table, the algorithms closest to Hoard are Vee and Hsu, DYNIX, and LKmalloc.... ..."