QGL.jl
A performance orientated QGL compiler.
Installation
The package is not yet registered with METADATA.jl and so must be cloned with
Pkg.clone("https://github.com/BBN-Q/QGL.jl.git")
Benchmarks
Preliminary benchmarks show speed-ups for Python QGL of ~25-30X.
In the absence of proper benchmarking and regression testing we use the 1 qubit
GST sequences from QGL issue #69 and
the sequence creation script in test/benchmark.jl. With q1 having 20ns
pulses and 100MHz sidebanding frequency and at commit 8fbbee6. Since it takes
5-6 seconds to compile and the default Benchmarking.jl times out with a single
run. There is some variation so it is worth running a few trials.
julia> using QGL
julia> q1 = Qubit("q1")
q1
julia> include("test/benchmark.jl")
create_1Q_GST_seqs
julia> seqs = create_1Q_GST_seqs("/home/cryan/Downloads/sequence_numbers.csv", q1);
julia> using BenchmarkTools
julia> t = @benchmark compile_to_hardware(seqs, "silly") samples=5 seconds=60
BenchmarkTools.Trial:
memory estimate: 1.56 gb
allocs estimate: 66356642
--------------
minimum time: 6.685 s (5.09% GC)
median time: 7.104 s (5.14% GC)
mean time: 7.091 s (5.26% GC)
maximum time: 7.373 s (5.65% GC)
--------------
samples: 5
evals/sample: 1
time tolerance: 5.00%
memory tolerance: 1.00%
License
Apache License v2.0
Funding
This work was funded in part by the Army Research Office under contract W911NF-14-C-0048.