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roflmaostc · Feb 11, 2024 · bfa7919 · bfa7919
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diff --git a/docs/Manifest.toml b/docs/Manifest.toml
@@ -58,9 +58,9 @@ version = "0.5.0"
 
 [[deps.ChainRulesCore]]
 deps = ["Compat", "LinearAlgebra"]
-git-tree-sha1 = "ab79d1f9754a3988a7792caec43bfdc03996020f"
+git-tree-sha1 = "ad25e7d21ce10e01de973cdc68ad0f850a953c52"
 uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
-version = "1.21.0"
+version = "1.21.1"
 weakdeps = ["SparseArrays"]
 
     [deps.ChainRulesCore.extensions]
@@ -297,22 +297,11 @@ git-tree-sha1 = "60e3045590bd104a16fefb12836c00c0ef8c7f8c"
 uuid = "458c3c95-2e84-50aa-8efc-19380b2a3a95"
 version = "3.0.13+0"
 
-[[deps.OrderedCollections]]
-git-tree-sha1 = "dfdf5519f235516220579f949664f1bf44e741c5"
-uuid = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
-version = "1.6.3"
-
 [[deps.PCRE2_jll]]
 deps = ["Artifacts", "Libdl"]
 uuid = "efcefdf7-47ab-520b-bdef-62a2eaa19f15"
 version = "10.42.0+1"
 
-[[deps.Parameters]]
-deps = ["OrderedCollections", "UnPack"]
-git-tree-sha1 = "34c0e9ad262e5f7fc75b10a9952ca7692cfc5fbe"
-uuid = "d96e819e-fc66-5662-9728-84c9c7592b0a"
-version = "0.12.3"
-
 [[deps.Parsers]]
 deps = ["Dates", "PrecompileTools", "UUIDs"]
 git-tree-sha1 = "8489905bcdbcfac64d1daa51ca07c0d8f0283821"
@@ -345,10 +334,10 @@ deps = ["InteractiveUtils", "Markdown", "Sockets", "Unicode"]
 uuid = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
 
 [[deps.RadonKA]]
-deps = ["Atomix", "ChainRulesCore", "FFTW", "IndexFunArrays", "KernelAbstractions", "Parameters", "PrecompileTools"]
+deps = ["Atomix", "ChainRulesCore", "FFTW", "IndexFunArrays", "KernelAbstractions", "PrecompileTools"]
 path = ".."
 uuid = "86de8297-835b-47df-b249-c04e8db91db5"
-version = "0.3.1"
+version = "0.6.0"
 
 [[deps.Random]]
 deps = ["SHA"]
@@ -428,11 +417,6 @@ uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 deps = ["Random", "SHA"]
 uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 
-[[deps.UnPack]]
-git-tree-sha1 = "387c1f73762231e86e0c9c5443ce3b4a0a9a0c2b"
-uuid = "3a884ed6-31ef-47d7-9d2a-63182c4928ed"
-version = "1.0.2"
-
 [[deps.Unicode]]
 uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
 

diff --git a/docs/src/benchmark.md b/docs/src/benchmark.md
@@ -1,14 +1,14 @@
-# Benchmark and Comparison with Matlab and Astra
+# Benchmark and Comparison with Matlab, Astra, torch-radon
 Tested on a AMD Ryzen 9 5900X 12-Core Processor with 24 Threads and a NVIDIA GeForce RTX 3060 with Julia 1.10.0 on Ubuntu 22.04.
 
 # Results
 
-|                   |RadonKA.jl CPU | RadonKA.jl GPU    | Matlab CPU | Astra CPU | Astra GPU |
-|-------------------|---------------|-------------------|------------|-----------|-----------|
-|2D sample - Radon  |1.1s           |0.07s              |0.39s       |7.0s       |0.025s     |
-|2D sample - Backprojection |1.4s           |0.50s              |0.37s       |6.4s       |N/A        |
-|3D sample - Radon  |7.4s           |0.28s              |9.01s       |N/A        |1.12s      |
-|3D sample - Backprojection |7.9s           |0.53s              |3.24s       |N/A        |N/A        |
+|                               |RadonKA.jl CPU | RadonKA.jl CUDA    | Matlab CPU | Astra CPU | Astra CUDA |torch-radon CUDA|
+|-------------------------------|---------------|-------------------|------------|-----------|-----------|----------------|
+|2D sample - Radon              |1.1s           |0.07s              |0.39s       |7.0s       |0.025s     |0.011s           | 
+|2D sample - Backprojection     |1.4s           |0.50s              |0.37s       |6.4s       |N/A        |0.008s           | 
+|3D sample - Radon              |7.4s           |0.28s              |9.01s       |N/A        |1.12s      |0.062s          |
+|3D sample - Backprojection     |7.9s           |0.53s              |3.24s       |N/A        |N/A        |0.063s          |
 
 
 
@@ -52,6 +52,48 @@ Tested on a AMD Ryzen 9 5900X 12-Core Processor with 24 Threads and a NVIDIA GeF
 ![](../assets/radonka_backproject.png)
 
 
+## torch-radon
+```python
+import torch
+import torch_radon
+
+
+volume = torch_radon.volumes.Volume2D()
+angles = torch.tensor(np.linspace(0, 2*np.pi, 500), dtype=torch.float32, device="cuda")
+sample = torch.rand(1,1920, 1920, device="cuda")
+radon = torch_radon.ParallelBeam(volume=volume, angles=angles, det_spacing=1.0, det_count=1920)
+
+
+%%timeit
+radon.forward(sample)
+torch.cuda.synchronize()
+
+sinogram = radon.forward(sample)
+
+%%timeit
+radon.backward(sinogram)
+torch.cuda.synchronize()
+
+
+
+angles = torch.tensor(np.linspace(0, 2*np.pi, 500), dtype=torch.float32, device="cuda")
+sample = torch.rand(100, 512, 512, device="cuda")
+radon = torch_radon.ParallelBeam(volume=volume, angles=angles, det_spacing=1.0, det_count=512)
+
+
+%%timeit
+radon.forward(sample)
+torch.cuda.synchronize()
+
+sinogram = radon.forward(sample)
+
+%%timeit
+radon.backward(sinogram)
+torch.cuda.synchronize()
+```
+
+
+
 ## Matlab (R2023a)
 ```matlab
 arr = single(imread("/tmp/sample.jpg")); 
@@ -158,7 +200,7 @@ np.copy(proj_data)
 
 rec_id = astra.data3d.create('-vol', vol_geom)
 
-# Set up the parameters for a reconstruction algorithm using the GPU
+# Set up the parameters for a reconstruction algorithm using the CUDA
 cfg = astra.astra_dict('BP3D_CUDA')
 cfg['ReconstructionDataId'] = rec_id
 cfg['ProjectionDataId'] = proj_id