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COMPAQ ES40 Benchmarks

Machine Description

COMPAQ ES40 rack

COMPAQ ES40

1.PCI cards, 2.Fans, 3.Diskette drive,
4.Removable media bays, 5.CD-ROM drive,
6.4-bay disk drive storage cages, 7.Control panel,
8.Fans, 9.CPUs, 10.Memory.

   

Model Number

COMPAQ Alpha Server ES40

Number of Processors

4

Processor Type

Alpha EV67 at 672 MHz

Operating System

Digital UNIX

FMS Memory

3 Gbytes

Number of Controllers

4

Disks per Controller

3

Problem and Results

Code Used

Example 11

Example 11

Example 11

Example 11

Example 11

Example 11

Date Started

03/10/2000

03/10/2000

03/10/2000

03/11/2000

03/12/2000

03/12/2000

Number of Equations

20,000

20,000

50,000

50,000

15,000

50,000

Number of Vectors

1

1

1

1

1

1

Matrix Sparsity

Full

Full

Full

Full

Full

Full

Matrix Symmetry

Symmetric

Symmetric

Symmetric

Symmetric

Nonsymmetric
with pivoting

Nonsymmetric
with pivoting

Data Type

16-byte Complex

16-byte Complex

16-byte Complex

16-byte Complex

16-byte Complex

16-byte Complex

FMS Parameter IALGOR

0 (Normal)

4 (Red. Ops.)

0 (Normal)

4 (Red. Ops.)

4 (Red. Ops.)

4 (Red. Ops.)

CPU Time (Hr:Min:Sec)

2:42:23

2:21:06

41:50:45

33:46:52

2:02:24

69:37:05

Wall Time (Hr:Min:Sec)

42:22

37:36

10:43:58

8:41:34

33:22

18:15:18

I/O Wait Time (Hr:Min:Sec)

0:49

1:22

6:29

5:50

1:50

13:17

Megaflops per Processor

1,094

1,260

1,106

1,370

1,225

1,330

Overall Megaflops

4,196

4,727

4,313

5,326

4,497

5,072

Parellel Speedup

3.83 out of 4

3.75 out of 4

3.90 out of 4

3.89 out of 4

3.67 out of 4

3.81 out of 4

NOTES:

  1. CPU Time is the total amount of User and System time used by all processors.
  2. Wall Time is the elapsed time measured on a dedicated machine. This includes the time spent processing and any time spent waiting for I/O to complete.
  3. I/O Wait Time is the total time spent waiting for I/O to complete that is not overlapped by asynchronous I/O.
  4. Megaflops per Processor is the theoretical number of floating point operations performed, divided by the CPU time. When reduced operation algorithms are used, this is based on the number of floating point operations that would have been performed by the traditional algorithm.
  5. Overall Megaflops is the total number of floating point operations performed, divided by the Wall Time.
  6. Parallel Speedup is overall increase in performance due to parallel processing.


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