### Table 2: Performance of out-of-core QR factorization on 64 processors using MB=NB=50.

1997

"... In PAGE 13: ... Note that without this extra reordering cost and assuming perfect speedup from 64 to 256 processors, the out-of-core solver incurs approximately a 18% overhead over in-core solvers ((3502 ? 290)=(681 4) 1:18). Table2 shows the runtime (in seconds) for the out-of-core QR factorization on the Intel Paragon. The eld lwork is the amount of temporary storage (number of double precision numbers) available to the out-of-core routine for panels X and Y.... ..."

### Table 2: Isoflop scalability for the Cholesky factorization (Gflops).

"... In PAGE 10: ...ith the theoretical model described in Section 3.3. 1 2 4 8 16 32 100 200 300 400 500 600 700 800 900 1000 Number of Processors Factorization time [sec] ScaLAPACK PLAPACK Our algorithm (a) IBM pSeries 690 1 2 4 8 16 32 0 500 1000 1500 2000 2500 Number of Processors Factorization time [sec] ScaLAPACK PLAPACK Our algorithm (b) HP-COMPAQ Alpha Server Figure 5: Isomemory scalability of the Cholesky factorization. Table2 measures the scalability in floating-point operations of both algorithms, that we name isoflop scalability. It shows how the performance per processor (in Gflops) of the algorithms behaves when the number of processors increases and while each processor performs the same number of floating-point operations.... In PAGE 10: ...8 1011 floating-point operations per processor. It can be seen in Table2 that the performance of the... ..."

### Table IV. Performance of Parallel Cholesky Factorization

2004

Cited by 8

### Table V. Genetic (First Panel), Shared Environmental (Second Panel), and Unique Environmental (Third Panel) Factor Loadings Estimated for the Full Cholesky Decompositiona

### TABLE 2 Effect of permutations on Cholesky factorization.

### Table 3.6: Results for the Cholesky factorization.

### Table 3: Performance of out-of-core Cholesky factorization on 64 processors using MB=NB=50.

1997

"... In PAGE 13: ... For large problems (and assuming perfect speedup), the out-of-core version incurs an overhead of around 16% over the in-core solver ((5466=4)=1176 1:16). Table3 shows the runtime (in seconds) for the out-of-core Cholesky factorization on the Intel Paragon. The eld lwork is the amount of temporary storage (number of double precision numbers) available to the out-of-core routine for panels X and Y.... ..."

Cited by 17

### Table 3: Performance of out-of-core Cholesky factorization on 64 processors using MB=NB=50.

"... In PAGE 13: ... For large problems (and assuming perfect speedup), the out-of-core version incurs an overhead of around 16% over the in-core solver ((5466=4)=1176 1:16). Table3 shows the runtime (in seconds) for the out-of-core Cholesky factorization on the Intel Paragon. The eld lwork is the amount of temporary storage (number of double precision numbers) available to the out-of-core routine for panels X and Y.... ..."