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Fix Izhikevich synaptic weights
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[ "For now, let's put this in the code as comments. Later, we'll document this better when pulled out into parameter files." ]
2016-11-15T18:37:52
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CONTRIBUTOR
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Need to also look at the units we use in the code, the difference between that and that Matlab reference code, and which makes sense for us to use. <!--- @huboard:{"order":12.966569759790357,"milestone_order":155,"custom_state":""} -->
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Move model-specific defaults from Global.h to appropriate model class
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[ "Should there even be defaults? Or should the simulator just refuse to run if parameter values aren't defined in a configuration XML file?\n", "@torisalvatore, I'll take over this. I'm going to look at consistency among default values anyway." ]
2016-10-21T21:59:44
2023-11-22T20:46:32
null
CONTRIBUTOR
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Right now, there are a bunch of defaults for various parameters of LIF neurons and DS synapses. After checking that it won't break anything, these should be moved.
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Compare PTX code for changeDSSynapsePSR() with and without assert()
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2016-07-26T20:15:19
2024-09-09T15:04:21
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Use commit 4b0738cf045ca0c14cab877fba4d222987725842, AllDSSynapses_d.cu to try the following: 1. Compile without the assert() to PTX code. 2. Compile with assert() How does the PTX code change? Is the code that calculates the psr value different?
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Create device configuration subsystem
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[ "Preliminarily, we are adding a number of threads per block member variable to the ClusterInfo object. However, that really should be calculated separately for each kernel. Need to think about what to store and where to enable this during system initialization." ]
2016-07-20T22:01:12
2021-04-02T00:52:30
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CONTRIBUTOR
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This should do the following: 1. Get information about simulation configuration (number of devices, which devices, which models, etc.) 2. Read device information for all requested devices 3. Allocate neurons to devices (incoming synapses live on the same device as their neuron) 4. Calculate threads per block, number of blocks per device. How do we specify the specific devices to use in a way that makes sense and will work on multiple machines (not just raiju or cerberus)? <!--- @huboard:{"custom_state":"","order":12.949077558904118,"milestone_order":145.0} -->
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Look into nvcc compiler options
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2016-06-01T20:47:21
2023-02-11T17:21:58
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CONTRIBUTOR
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For example, we should be using a virtual architecture switch for the -arch option. See [Options for Steering GPU Code Generation](http://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/#options-for-steering-gpu-code-generation) in the CUDA documentation. <!--- @huboard:{"order":146.5} -->
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Look into places where GPU and single-threaded code doesn't have exactly mirrored architectures
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2016-05-23T20:09:45
2021-04-02T00:53:18
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For example, the GPU version doesn't have a AllSynapsesDevice class. This might be fine, but such inconsistencies are something to think about.
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Clarify comment for ConnGrowth::updateSynapsesWeights()
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2016-05-16T21:14:50
2020-08-17T16:39:46
2020-08-17T16:39:46
CONTRIBUTOR
null
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Right now, it indicates it updates weights. This should be clarified to indicated that it takes a weight matrix already computed and is merely pushing those weights into the synapse data structures that are sitting on the device(s)
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Not identical results between cssgpu01 (Tesla M2090) and cssgpu02p (Tesla K80)
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[ "Hmm. I wonder if this might reflect the fact that there are more streaming processors per streaming multiprocessor (so threads in a warp aren't sharing streaming processors), or more processors overall (so more blocks can run simultaneously)? Perhaps that causes different sequences of random numbers to arrive at c...
2016-05-11T23:44:52
2024-09-09T15:04:37
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NONE
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Run the same description file () on cssgpu01 and cssgpu02p. The results were not identical.
null
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Fix command line arguments and help messages
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2016-05-05T22:03:28
2020-08-11T23:55:22
2020-08-11T23:55:22
CONTRIBUTOR
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<!--- @huboard:{"order":57.973907248405304,"milestone_order":135,"custom_state":""} -->
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Add an "install" target to Makefile
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[ "Let's see if we can finalize this in CMake. It should also make sure that it copies over runtimes files.", "This is the follow-on to the out-of-source build." ]
2016-05-05T22:02:52
2024-05-14T17:10:51
null
CONTRIBUTOR
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With the idea that BG and config files get copied elsewhere, so runs don't "pollute" the git development directory.
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Consider how/if to package releases to make adaptation easier for users
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2016-04-21T21:23:59
2020-07-25T19:19:01
null
CONTRIBUTOR
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Segregate files that would be modified from those that don't? Precompile parts of the system? <!--- @huboard:{"order":132.75} -->
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Think about abstracting random number generation for its multiple uses
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2016-04-14T21:05:38
2021-04-02T00:11:53
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1. On the CPU, during simulation setup, for initializing parameters. 2. On the CPU, for CPU-based simulations, for noise. 3. On the GPU, for GPU-based simulations, for noise.
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Fix random number generator seeding
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[ "It will be critical to ensure that we can seed the RNGs with states that are identical with what happens in BrainGrid, for cross-validation." ]
2016-04-14T21:02:20
2021-08-03T03:10:09
2021-08-03T03:10:09
CONTRIBUTOR
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There are two (sets of) RNG: rng in Globals.cpp, which is used to randomize parameters during setup, and is seeded with a hard-coded constant, and rgNormrnd/GPU Mersenne twister RNG(s) (created in SingleThreadedSpikingModel.cpp or GPUSpikingModel.cu), used to generate noise during simulation. The latter is seeded from the parameter file; the former is not.
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Variable renaming needed in GPUSpikingModel::setupSim()
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[ "Of course, that may trigger a minor refactor elsewhere, but these are all local variables that shouldn't cause issues outside that method.\n", "@apw6 , you're going to have to modify this method anyway, so you might as well take care of this. So, I guess you aren't given a break.\n", "Is this fixed?" ]
2016-03-15T23:14:37
2021-04-02T00:13:17
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CONTRIBUTOR
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Clean up the following: `//initialize Mersenne Twister` `//assuming neuron_count >= 100 and is a multiple of 100. Note rng_mt_rng_count must be <= MT_RNG_COUNT` `int rng_blocks = 25; //# of blocks the kernel will use` `int rng_nPerRng = 4; //# of iterations per thread (thread granularity, # of rands generated per thread)` `int rng_mt_rng_count = sim_info->totalNeurons/rng_nPerRng; //# of threads to generate for neuron_count rand #s` `int rng_threads = rng_mt_rng_count/rng_blocks; //# threads per block needed`
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cuda/GPUSpikingModel.h: declarations of MTGPU functions should be included from elsewhere
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[ "Just to clarify, those declarations are now in Core/GPUSpikingModel.h, but should be moved to a file such as MersenneTwister_d.h. Currently, that file seems to be relevant only to the code in MersenneTwister_d.cu. Double-check that -- does any of that stuff belong in an externally-facing .h file?" ]
2016-03-15T23:09:15
2020-08-06T00:46:24
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There should be a .h file for MersenneTwister_kernel.cu that declares its functions that can be called by external code. <!--- @huboard:{"order":112.75} -->
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rng/Norm.h: Norm class should inherit from MTRand
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[ "Fixed in BrainGrid since ~June 2016" ]
2016-03-15T22:28:18
2021-07-22T18:02:54
2021-07-22T18:02:54
CONTRIBUTOR
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Right now, there is a #define in MersenneTwister.h, which should be removed, because it's really almost impossible to figure out what's going on with this code (and I'm sure that Doxygen can't figure this out). <!--- @huboard:{"order":112.71875,"milestone_order":111} -->
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Evolve framework to have separate abstract base classes for neuron, synapse, connection modification, and external input
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[ "@fumik , I know you've been doing some refactoring. Is it the case that what you've done basically accomplishes all or part of this? Does it render this moot?\n", "Yes, adding new neurons, synapses, and connections models, we need to modify the current class structure. I'm simultaneously working on this issue an...
2014-11-26T18:12:12
2020-07-23T00:33:07
2020-07-23T00:33:07
CONTRIBUTOR
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Look to repository from brett-etal07 for benchmark networks to implement
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[ "This is for future information. More immediately (as of November 2014), we will focus on the Izhikevich model from his 2006 paper.\n" ]
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See https://senselab.med.yale.edu/ModelDB/showmodel.asp?model=83319 <!--- @huboard:{"custom_state":"ready","order":12.973621882178792,"milestone_order":80} -->
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Optimize variables in AllNeurons and AllSynapses
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[ "**constant** variables need to be at the top level in the .cu file! because they generate code that allocates and initializes constant memory on the GPU. But that is not the case for ordinary host side variables that contain device side addresses.\n\nRight now, shared constants are actually allocated for each syna...
2014-05-05T23:12:40
2021-10-19T19:51:14
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@fumik added comments on AllNeurons.h and AllSynapses.h. There are four types of structure members, LOCAL CONSTANT, LOCAL VARIABLE, GLOBAL CONSTANT, and GLOBAL VARIABLE. All GLOBAL members can be scalars, not arrays. Also some structure members are neuron or synapse type dependent, so they can be optimized. <!--- @huboard:{"custom_state":"ready","order":12.97353066767093,"milestone_order":63} -->
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SparseMatrix operator()
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2014-01-22T01:05:40
2021-04-02T00:09:31
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SparseMatrix::operator() creates a zero value element if the element doesn't exist. This appears to violate the spirit of what a sparse matrix should be. On the other hand, it isn't immediately clear what else to do if you want to use this as an Lvalue. Perhaps there is no better option. But, a const accessor version is an obvious approach to partially ameliorate this. Then again, I don't remember what was going through my mind at the time and we don't want to assume I was completely confused at the time (no comments from the peanut gallery, please). Needs to be investigated thoroughly; maybe I will need to do this.
null
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Intelligent GPU query/configuration capability
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[ "This will be especially important as we move to support multiple GPUs, so it makes sense to get it working with a single GPU first.\n", "Probably should be generalized as applying to any situation with multiple computing resources, including multicore." ]
2013-11-14T16:27:31
2025-01-10T22:01:56
null
CONTRIBUTOR
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Can we automate determining number of threads per block, etc. based on GPU capabilities? We should certainly, at least, query the GPU capabilities and gracefully exit, with informative feedback, if those capabilities don't match simulation requirements. <!--- @huboard:{"custom_state":"","order":12.948915707573482,"milestone_order":37} -->
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Improved debugging tools
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[ "A promising framework is [log4cplus](http://sourceforge.net/p/log4cplus/wiki/Home/).\n" ]
2013-11-14T16:25:39
2020-08-16T23:42:16
2020-08-16T23:42:16
CONTRIBUTOR
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Perhaps leverage an open source C++ debug framework? <!--- @huboard:{"milestone_order":36.0} -->
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Implement an abstract RNG as a utility available to simulator developers
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[ "I think the focus here should be on having the ability to implement it differently, to take advantage of hardware capabilities (or improvements in parallel libraries), or to support RNGs with different distributions (normal, uniform, Poisson). Not a top priority right at this moment.\n", "I've created a new mile...
2012-12-06T15:26:13
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Pulled this issue from an e-mail Don sent.
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