Search found 275 matches

by Stan Tomov
Wed Mar 11, 2020 4:54 pm
Forum: User discussion
Topic: Limitations on precision
Replies: 5
Views: 152

Re: Limitations on precision

You may also want to try the 2-stage reduction algorithms, e.g. ./testing_dsyevdx_2stage -JV --niter 2 -n 7000 These are much faster especially for the large sizes that you target. Maybe also using multiple GPUs would help (adding "--ngpu 4" option). Also, you can try with ESSL. There is make.inc ex...
by Stan Tomov
Wed Mar 11, 2020 1:04 pm
Forum: User discussion
Topic: Limitations on precision
Replies: 5
Views: 152

Re: Limitations on precision

Some of these errors seem to be large and inconsistent. This is what I get on one of our systems with V100 and Intel CPU. [tomov@a04 testing]$ ./testing_dsyevd -JV --niter 5 -c -l -n 7000 % MAGMA 2.5.2 svn compiled for CUDA capability >= 7.0, 32-bit magma_int_t, 64-bit pointer. % CUDA runtime 9020, ...
by Stan Tomov
Tue Feb 25, 2020 12:51 pm
Forum: User discussion
Topic: External GPU on thunderbolt - and CUDA/MAGMA?
Replies: 2
Views: 277

Re: External GPU on thunderbolt - and CUDA/MAGMA?

I am not sure about the exact mechanism of connecting them and what GPUs can be used as eGPUs, but if one makes the setup the issues of using the GPUs will be similar to systems where you have powerful GPUs connected to a "slow" host CPU (due to slow CPU or slow CPU-GPU data transfers). MAGMA can be...
by Stan Tomov
Tue Feb 25, 2020 12:13 pm
Forum: User discussion
Topic: Very large sparse eigensolves
Replies: 2
Views: 156

Re: Very large sparse eigensolves

Looks like you need about 15 GB just for the matrix. You could use MAGMA and 32GB GPU to solve such problems. MAGMA implements the LOBPCG method, but that has to be adjusted for your problem - the matrix has to be definite and you would look for the smallest (or largest) eigenstates. One way is fold...
by Stan Tomov
Tue Jan 07, 2020 11:36 am
Forum: User discussion
Topic: Best library for O(100k) linear system
Replies: 2
Views: 366

Re: Best library for O(100k) linear system

Dear Radek,
You can try the SLATE library:
https://bitbucket.org/icl/slate/
which provides the ScaLAPACK functionalities with support for GPU use.
Stan
by Stan Tomov
Wed Dec 18, 2019 12:56 am
Forum: User discussion
Topic: low performance running mixed precision lu factorization
Replies: 11
Views: 677

Re: low performance running mixed precision lu factorization

The slow CPU will affect performance since MAGMA still uses CPUs for part of the computation. We can tune for this case or use other codes that are GPU only, but these are not connected yet to the mixed-precision solvers.
by Stan Tomov
Tue Dec 17, 2019 11:57 pm
Forum: User discussion
Topic: testing_dsymv halts with "Killed"
Replies: 2
Views: 263

Re: testing_dsymv halts with "Killed"

This is most probably due to running out of memory. The magma tester checks error codes around the allocations and that should have printed if the allocation can not be made, but I wonder if CUDA tried to use some more memory later the allocation, and couldn't so killed the program. On my laptop for...
by Stan Tomov
Thu Dec 12, 2019 10:36 am
Forum: User discussion
Topic: low performance running mixed precision lu factorization
Replies: 11
Views: 677

Re: low performance running mixed precision lu factorization

Now I see MAGMA is not compiled for Volta, e.g., the tester above prints % MAGMA 2.5.1 compiled for CUDA capability >= 3.0, 32-bit magma_int_t, 64-bit pointer. Can you please modify your make.inc file, and in particular, add the GPU_TARGET. After #GPU_TARGET ?= Kepler Maxwell Pascal add GPU_TARGET =...
by Stan Tomov
Thu Dec 12, 2019 2:08 am
Forum: User discussion
Topic: low performance running mixed precision lu factorization
Replies: 11
Views: 677

Re: low performance running mixed precision lu factorization

MKL is the Intel Math Kernel Library. It provides highly optimized routines that MAGMA uses on the CPU. You can download it from here: https://software.intel.com/en-us/mkl/choose-download/linux After you install it, set environment variable MKLROOT to where the MKL is installed, go to the main magma...
by Stan Tomov
Wed Dec 04, 2019 12:36 am
Forum: User discussion
Topic: magma_init returns MAGMA_SUCCESS with no GPU
Replies: 1
Views: 284

Re: magma_init returns MAGMA_SUCCESS with no GPU

One of the functions of magma_init() is to determine how many devices are out there. If there are none, the number of devices is initialized as 0. The code that checks this looks like this: err = cudaGetDeviceCount( &g_magma_devices_cnt ); if ( err != 0 && err != cudaErrorNoDevice ) { info = MAGMA_E...