This is a collection of simple streaming kernels.
Apart from the micro-benchmark functionality this is also a blueprint for other micro-benchmark applications.
It contains C modules for:
- Aligned data allocation
- Query and control affinity settings
- Accurate timing
Moreover the benchmark showcases a simple generic Makefile that can be used in other projects.
The benchmark is heavily inspired by John McCalpin's https://www.cs.virginia.edu/stream/ benchmark.
It contains the following streaming kernels with corresponding data access pattern (Notation: S - store, L - load, WA - write allocate). All variables are vectors, s is a scalar:
- init (S1, WA): Initilize an array:
a = s
. Store only. - sum (L1): Vector reduction:
s += a
. Load only. - copy (L1, S1, WA): Classic memcopy:
a = b
. - update (L1, S1): Update vector:
a = a * scalar
. Also load + store but without write allocate. - triad (L2, S1, WA): Stream triad:
a = b + c * scalar
. - daxpy (L2, S1): Daxpy:
a = a + b * scalar
. - striad (L3, S1, WA): Schoenauer triad:
a = b + c * d
. - sdaxpy (L3, S1): Schoenauer triad without write allocate:
a = a + b * c
.
As added benefit the code is a blueprint for a minimal benchmarking application with a generic makefile and modules for aligned array allocation, accurate timing and affinity settings. Those components can be used standalone in your own project.
- Configure the toolchain and additional options in
config.mk
:
# Supported: GCC, CLANG, ICC
TAG ?= GCC
ENABLE_OPENMP ?= false
ENABLE_LIKWID ?= false
OPTIONS = -DSIZE=120000000ull
OPTIONS += -DNTIMES=10
OPTIONS += -DARRAY_ALIGNMENT=64
#OPTIONS += -DVERBOSE_AFFINITY
#OPTIONS += -DVERBOSE_DATASIZE
#OPTIONS += -DVERBOSE_TIMER
The verbosity options enable detailed output about affinity settings, allocation sizes and timer resolution.
Notice: OpenMP involves significant overhead through barrier cost, especially on systems with many memory domains. The default problem size is set to almost 4GB to have enough work vs overhead. If you suspect that the result should be better you may try to further increase the problem size. To compare to original stream results on X86 systems you have to ensure that streaming store instructions are used. For the ICC toolchain this is now the default (Option -qopt-streaming-stores=always
).
- Build with:
make
You can build multiple toolchains in the same directory, but notice that the Makefile is only acting on the one currently set. Intermediate build results are located in the <TOOLCHAIN>
directory.
To output the executed commands use:
make Q=
- Clean up with:
make clean
to clean intermediate build results.
make distclean
to clean intermediate build results and binary.
- (Optional) Generate assembler:
make asm
The assembler files will also be located in the <TOOLCHAIN>
directory.
To run the benchmark call:
./bwBench-<TOOLCHAIN>
The benchmark will output the results similar to the stream benchmark. Results are validated. For threaded execution it is recommended to control thread affinity.
We recommend to use likwid-pin for benchmarking:
likwid-pin -c 0-3 ./bwbench-GCC
Example output for threaded execution:
-------------------------------------------------------------
[pthread wrapper]
[pthread wrapper] MAIN -> 0
[pthread wrapper] PIN_MASK: 0->1 1->2 2->3
[pthread wrapper] SKIP MASK: 0x0
threadid 140271463495424 -> core 1 - OK
threadid 140271455102720 -> core 2 - OK
threadid 140271446710016 -> core 3 - OK
OpenMP enabled, running with 4 threads
----------------------------------------------------------------------------
Function Rate(MB/s) Rate(MFlop/s) Avg time Min time Max time
Init: 22111.53 - 0.0148 0.0145 0.0165
Sum: 46808.59 46808.59 0.0077 0.0068 0.0140
Copy: 30983.06 - 0.0207 0.0207 0.0208
Update: 43778.69 21889.34 0.0147 0.0146 0.0148
Triad: 34476.64 22984.43 0.0282 0.0278 0.0305
Daxpy: 45908.82 30605.88 0.0214 0.0209 0.0242
STriad: 37502.37 18751.18 0.0349 0.0341 0.0388
SDaxpy: 46822.63 23411.32 0.0281 0.0273 0.0325
----------------------------------------------------------------------------
Solution Validates