diff options
Diffstat (limited to 'spires_memristor_sim')
| -rw-r--r-- | spires_memristor_sim/README.md | 24 | ||||
| -rw-r--r-- | spires_memristor_sim/requirements.txt | 71 | ||||
| -rw-r--r-- | spires_memristor_sim/spires_interface.py | 116 | ||||
| -rw-r--r-- | spires_memristor_sim/torch_reservoir.py | 68 |
4 files changed, 0 insertions, 279 deletions
diff --git a/spires_memristor_sim/README.md b/spires_memristor_sim/README.md deleted file mode 100644 index e5717b6..0000000 --- a/spires_memristor_sim/README.md +++ /dev/null @@ -1,24 +0,0 @@ -# Spires reservoir simulated on memristor crossbar using memTorch - -## overview -### simulation -Here we are using both memTorch and the Spiresrc libraries working together to simulate -a spires reservoir on a memristor crossbar. memTorch is acting as the weights, simulating -at a physics level including device to device differences, conductance drag, etc.... -Spires is acting as the actual reservoir neurons and determining the spikes. - -### benchmark - -## setup - - -## Goal -The goal is to able to simulate a spires reservoir on a memristor crossbar using -a custom memristor spice model(HIL), thus you can run multiple simulations with -multiple models to compare how each performs using benchmark results. - -## task -The plan right now is to give the cart-pole task for benchmarking. - -## metrics - diff --git a/spires_memristor_sim/requirements.txt b/spires_memristor_sim/requirements.txt deleted file mode 100644 index c9b7376..0000000 --- a/spires_memristor_sim/requirements.txt +++ /dev/null @@ -1,71 +0,0 @@ -asteval==1.0.9 -asttokens==3.0.1 -contourpy==1.3.3 -cuda-bindings==13.3.1 -cuda-pathfinder==1.5.5 -cuda-toolkit==13.0.2 -cycler==0.12.1 -decorator==5.3.1 -dill==0.4.1 -executing==2.2.1 -filelock==3.29.4 -fonttools==4.63.0 -fsspec==2026.6.0 -ipython==9.15.0 -ipython_pygments_lexers==1.1.1 -jedi==0.20.0 -Jinja2==3.1.6 -joblib==1.5.3 -kiwisolver==1.5.0 -lmfit==1.3.4 -MarkupSafe==3.0.3 -matplotlib==3.11.0 -matplotlib-inline==0.2.2 -memtorch-cpu==1.1.6 -mpmath==1.3.0 -narwhals==2.22.1 -networkx==3.6.1 -numpy==2.5.0 -nvidia-cublas==13.1.1.3 -nvidia-cuda-cupti==13.0.85 -nvidia-cuda-nvrtc==13.0.88 -nvidia-cuda-runtime==13.0.96 -nvidia-cudnn-cu13==9.20.0.48 -nvidia-cufft==12.0.0.61 -nvidia-cufile==1.15.1.6 -nvidia-curand==10.4.0.35 -nvidia-cusolver==12.0.4.66 -nvidia-cusparse==12.6.3.3 -nvidia-cusparselt-cu13==0.8.1 -nvidia-nccl-cu13==2.29.7 -nvidia-nvjitlink==13.0.88 -nvidia-nvshmem-cu13==3.4.5 -nvidia-nvtx==13.0.85 -packaging==26.2 -pandas==3.0.4 -parso==0.8.7 -pexpect==4.9.0 -pillow==12.2.0 -prompt_toolkit==3.0.52 -psutil==7.2.2 -ptyprocess==0.7.0 -pure_eval==0.2.3 -Pygments==2.20.0 -pyparsing==3.3.2 -python-dateutil==2.9.0.post0 -scikit-learn==1.9.0 -scipy==1.18.0 -seaborn==0.13.2 -setuptools==81.0.0 -six==1.17.0 -sklearn==0.0.post12 -stack-data==0.6.3 -sympy==1.14.0 -threadpoolctl==3.6.0 -torch==2.12.1 -torchvision==0.27.1 -traitlets==5.15.1 -triton==3.7.1 -typing_extensions==4.15.0 -uncertainties==3.2.3 -wcwidth==0.8.1 diff --git a/spires_memristor_sim/spires_interface.py b/spires_memristor_sim/spires_interface.py deleted file mode 100644 index b7e5fff..0000000 --- a/spires_memristor_sim/spires_interface.py +++ /dev/null @@ -1,116 +0,0 @@ -import ctypes -import numpy -import torch -import random - -LIF_DISCRETE = 0 - -#load the spires library -spires_lib = ctypes.CDLL("../spires/lib/libspires.so") - -# C signautes for creating reservoir -spires_lib.create_reservoir.argtypes = [ - ctypes.c_size_t, - ctypes.c_size_t, - ctypes.c_size_t, - ctypes.c_double, - ctypes.c_double, - ctypes.c_double, - ctypes.c_double, - ctypes.c_double, - ctypes.c_int, - ctypes.c_int, - ctypes.POINTER(ctypes.c_double) -] -spires_lib.create_reservoir.restype = ctypes.c_void_p - -# C signatures for reservoir destruction -spires_lib.free_reservoir.argtypes = [ctypes.c_void_p] -spires_lib.free_reservoir.restype = None - -# C signatures for step reservoir function -spires_lib.update_neuron.argtypes = [ - ctypes.c_void_p, #Pointer to spires reservoir struct - ctypes.c_int, - ctypes.c_double, - ctypes.c_double -] -spires_lib.update_neuron.restype = None - -# C signatures for get neuron spike function -spires_lib.read_reservoir_spikes.argtypes = [ - ctypes.c_void_p, - ctypes.POINTER(ctypes.c_float) -] -spires_lib.read_reservoir_spikes.restype = None - -def init_spires_reservoir(reservoir_size): - print("Creating spires reservoir") - - neuron_parameters = (ctypes.c_double * 4)(0.0, 1.0, 0.2, 0.5) - c_neuron_parameters = ctypes.cast(neuron_parameters, ctypes.POINTER(ctypes.c_double)) - - reservoir_ptr = spires_lib.create_reservoir( - ctypes.c_size_t(int(reservoir_size)), # num neurons - ctypes.c_size_t(int(reservoir_size)), # num neurons - ctypes.c_size_t(2), # num_outputs - ctypes.c_double(0.9), # spectral radius - ctypes.c_double(0.8), # ei_ratio - ctypes.c_double(1.0), # input_strength - ctypes.c_double(0.1), # connectivity - ctypes.c_double(1.0), # dt - ctypes.c_int(1), # connectivity type ( 1 = sparse) - ctypes.c_int(LIF_DISCRETE), # neuron type - c_neuron_parameters # neuron params - ) - - #allocate empty void pointer, (reservoir will go here) - if not reservoir_ptr: - raise RuntimeError(f"Spires faile to initialize the reservoir: {status_code}") - else: - print("Spires reservoir initialized") - - # reservoir_ptr._keep_alive = neuron_parameters - - return reservoir_ptr - -def free_spires_reservoir(reservoir_ptr): - print("Freeing the spires reservoir") - spires_lib.free_reservoir(reservoir_ptr) - return 0 - - -#change currents from tensor to a flat C pointer array for spires to read -def send_currents_to_spires(reservoir_ptr, currents_tensor): - print("Sending currents to spires") - # ----- extract from pytorhc graph ----- - # .detach() removes it from auto gradient tracking - # .cpu() make sure data is in RAM, not VRAM - # .numpy() maps it to numpy array - # ----- makes suren layout matches 64 bit double C-array ----- - # .astype(npfloat64) forces standard CC float precistion - # .flatten() makes sure the memory is a 1D block - numpy_array = currents_tensor.detach().cpu().numpy().astype(numpy.float64).flatten() - - some_ptr = ctypes.cast(reservoir_ptr, ctypes.POINTER(ctypes.POINTER(ctypes.c_void_p))) - - neurons_array = some_ptr[0] - - print("updating the neurons") - for i in range(len(numpy_array)): - neuron_ptr = neurons_array[i] - input_current = numpy_array[i] - - spires_lib.update_neuron(neuron_ptr, LIF_DISCRETE, input_current, 1.0) - - return numpy_array - -def read_spikes_from_spires(reservoir_ptr, size=0): - print("Recieved spikes from spires") - #didnt do any safety checking womp womp - returned_spikes = numpy.zeros(size, dtype=numpy.float64) - c_spike_ptr = returned_spikes.ctypes.data_as(ctypes.POINTER(ctypes.c_float)) - - spires_lib.read_reservoir_spikes(reservoir_ptr, c_spike_ptr) - - return returned_spikes diff --git a/spires_memristor_sim/torch_reservoir.py b/spires_memristor_sim/torch_reservoir.py deleted file mode 100644 index 9d58d43..0000000 --- a/spires_memristor_sim/torch_reservoir.py +++ /dev/null @@ -1,68 +0,0 @@ -import torch -import memtorch -from spires_interface import ( - free_spires_reservoir, - init_spires_reservoir, - send_currents_to_spires, - read_spikes_from_spires, -) - -NUM_INPUTS = 4 -NUM_OUTPUTS = 4 -NUM_NEURONS = 800 - -input_layer = torch.nn.Linear(NUM_INPUTS, NUM_NEURONS, bias=False) -#this is a recurrent layer sort of??? -reservoir_layer = torch.nn.Linear(NUM_NEURONS, NUM_NEURONS, bias=False) -readout_layer = torch.nn.Linear(NUM_NEURONS, NUM_OUTPUTS, bias=False) - -spires_reservoir = init_spires_reservoir(NUM_NEURONS) - -#make the reservoir sparse and random -with torch.no_grad(): - reservoir_layer.weight.data.normal_(0.0, 0.5) #random weight - - #mask so 10% of connections exist - mask = (torch.rand(NUM_NEURONS, NUM_NEURONS) < 0.10).float() - reservoir_layer.weight.data *= mask - -# patch layers into memristor crossbars with memTorch -memristor_model = memtorch.bh.memristor.VTEAM -memristor_model_params = { - 'time_series_resolution': 1e-3, - 'r_on': 50, - 'r_off': 1000, -} - -mem_input_layer = memtorch.mn.Module.patch_model( - input_layer, - memristor_model, - memristor_model_params, -) - -mem_reservoir_layer = memtorch.mn.Module.patch_model( - reservoir_layer, - memristor_model, - memristor_model_params, -) - -#run spiking loop with spires -previous_spikes = torch.zeros(1, NUM_NEURONS) -for step in range(500): - cartpole_state = [0, 1, 2, 3] #this isn't final - input_tensor = torch.tensor(cartpole_state).float().unsqueeze(0) - currents_in = mem_input_layer(input_tensor) - - currents_recv = mem_reservoir_layer(previous_spikes) - - #may need to scale currents? - total_currents = currents_in + currents_recv - - send_currents_to_spires(spires_reservoir, total_currents) - - current_spikes_np = read_spikes_from_spires(spires_reservoir, NUM_NEURONS) - previous_spikes = torch.from_numpy(current_spikes_np).float().unsqueeze(0) - -free_spires_reservoir(spires_reservoir) -#pass current spikes np to readout layer - |