However, a computer's performance when running actual applications is likely to be far behind the maximal performance it achieves running the appropriate LINPACK benchmark. The performance measured by the LINPACK benchmark consists of the number of 64-bit floating-point operations, generally additions and multiplications, a computer can perform per second, also known as FLOPS. The performance of a computer is a complex issue that depends on many interconnected variables. The actual performance will always be lower than the peak performance. The peak performance is the maximal theoretical performance a computer can achieve, calculated as the machine's frequency, in cycles per second, times the number of operations per cycle it can perform. Nevertheless, the LINPACK benchmark performance can provide a good correction over the peak performance provided by the manufacturer. It is a simplification, since no single computational task can reflect the overall performance of a computer system. The aim is to approximate how fast a computer will perform when solving real problems. The latest version of these benchmarks is used to build the TOP500 list, ranking the world's most powerful supercomputers. Introduced by Jack Dongarra, they measure how fast a computer solves a dense n by n system of linear equations Ax = b, which is a common task in engineering. The LINPACK Benchmarks are a measure of a system's floating point computing power.
Jack Dongarra, Jim Bunch, Cleve Moler, and Gilbert Stewart You should also have a look at the original High Performance LINPACK.For other uses, see LINPACK (disambiguation). With larger pages it might make sense to set this value to a large number, e.g. Once again to use the cache efficiently it is advised to have all arrays start at the boundary of memory pages. Often n is selected to be the smallest integer divisible by 8 that is greater than N. Do avoid this it is advised to set n>N inserting some padding between the column data. The reason is that when n=N the algorithm running in several parallel threads may run into a phenomenon known as cache thrashing. Note that we use a different symbol n instead of N. This is equivalent to solving a vector equation Ax=b where x and b are N-dimensional vectors and A is an N*N matrix.Īn N*N matrix is represented in the memory as an N*N array where individual columns are stored at offsets 0, n, 2*n etc. Linpack benchmark solves a system of N simultaneous linear equations. The parameters that you seem to be confused are all related to the way matrices are represented and accessed. This is the setup for Intel optimized Linpack benchmark. The best performance is likely to be obtained when arrays are aligned to the page size boundary.
But maybe easier would be to start by just trying the example input file: "linpack_xeon64.exe < lininput_xeon64".
You can run "linpack_xeon64.exe -e" to get a length discussion of parameters and what combinations are best. Sounds like linpack_xeon64.exe is the right benchmark for you. There is quite a bit of good information in the benchmarkslinpack directory. I am sorry to bother you with this most likely basic question but i would apreciate any help given.
It is asking for several inputsĬould you please explain to me how to calculate these values and what they mean? I have downloaded and installed the Linpack benchmark suite and executed it. In my case its a 64bit dual xeon platform with 8GB of main memory. If i understood correctly the Linpack App uses the Intel optimized librarys for the architecture to be tested. and got moved to my new department, so please excuse my beginner questions and my english since this is not my native language. About a week ago i received my first WS system and have to use the Linpack Suite to test it. It has become a part of my responsibility at work to certify Workstation system for the Energy Star. My name is Florian and i have some basic questions for you about the Linpack Benchmark App.