css 700: mass cuda parallel‐computing library for multi‐agent spatial simulation fall quarter...

UW Bothell Computing & Software Systems

CSS 700: MASS CUDAParallel Computing Library for Multi Agent Spatial Simulation‐ ‐

Fall Quarter 2014Nathaniel Hart

UW Bothell Computing & Software Systems 2

Project Milestones

M1: The ability to execute simulations that fit on a single device. Initial focus is on creating the command & control logic with hooks to add multi-device functionality later

M2: The ability to execute simulations that fit on multiple devices. This will require extensible border exchange logic.

M3: The ability to execute simulations that exceed the memory of a host’s available devices. This means a great deal of the partition and border exchange logic.


Quarter Goals (M1)Date Range Activity Deliverable9/15/14 - 10-/15/14

Specify MASS CUDA Architecture and single-GPU implementation

Specifications for algorithms and design choices for phase I implementation

10/16/14 - 12/15/14 Implement part I of MASS AgentsDesign multi-GPU communication algorithms

A minimally viable version of the MASS CUDA that can run a simulation of size not exceeding available memory on a single GPU.

A version of the MASS CUDA library suitable for use in CSS 534

Performance statistics for this initial implementation

Specifications for algorithms and design choices for phase II implementation


Project Status

M1 Status

Finished Unfinished

Code Completion

Finished Unfinished


Status Details

• Still need to lock down final ghost space solution for Agents• Debugging is now possible on Hercules• Need to talk to Jason to figure out how to remote in via GUI


Blocking Issues

• Hercules 2 is still not operational. Depends on Chris Fox to unblock.• Places will not instantiate properly


Virtual Functions

Image Source:http://www.learncpp.com/cpp-tutorial/125-the-virtual-table/


The Workaround

__global__ void createPlaces(Places ** places, int qty){

int idx = blockIdx.x * blockDim.x + threadIdx.x;

if(idx < qty){

// virtual function table created on GPU

places[idx] = new PlaceImpl();

}

}


Old ArchitectureUser Application

Dispatcher

Places Mass Agents

Places Partition[0]

Places Partition[n]

Agents Partition[0]

Agents Partition[n]

DeviceConfig[0] DeviceConfig[1] DeviceConfig[n]

API

Model Layer

User Layer

Command & Control Layer

Hardware


New ArchitectureUser

Application

Places

Mass

AgentsDeviceConfig [1]

Dispatcher

DeviceConfig [0] PlacesModel

Model

AgentsModel

Passes Calls To

Returns State Returns State

Manipulates

API calls & return values


The New Problem

• Instances created on the GPU can not be copied to the host and used for analysis.• Just as we break the virtual function table copying from the host to

the GPU, we cannot copy from the GPU to the host.


The New Workaround

Place

+ void callAll(int funcID, void *arg)+ void update( )

+ etc....

State

+ int x+ Agent *agents[10]+ etc....- State *myState


The New Workaround

Place ** h_ptrs

placeObjects 43210

MyState *h_state 43210

Place ** d_ptrs

placeObjects 43210

MyState *d_state 43210

HOST DEVICE


Big TODO’s

1. Refactor existing code to allow for place instantiation and separation of behavior and state

2. Implement all control kernel functions3. Write more tests


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css 700: mass cuda parallel‐computing library for multi‐agent spatial simulation fall quarter...

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