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Monte Carlo Option Pricing with multi-GPU support 
This sample evaluates fair call price for a given set of European options using the Monte Carlo approach, taking advantage of all CUDA-capable GPUs installed in the system. This sample use double precision hardware if a GTX 200 class GPU is present. |
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or later
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Matrix Transpose 
Efficient matrix transpose. |
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or later
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Clock 
This example shows how to use the clock function to measure the performance of kernel accurately. |
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or later
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Aligned Types 
A simple test, showing huge access speed gap between aligned and misaligned structures. |
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or later
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Parallel Reduction 
A parallel sum reduction that computes the sum of large arrays of values. This sample demonstrates several important optimization stratezies for parallel algorithms like reduction. |
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or later
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asyncAPI 
This sample uses CUDA streams and events to overlap execution on CPU and GPU. |
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or later
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simpleStreams 
This sample uses CUDA streams to overlap kernel executions with memcopies between the device and the host. Requires Compute Capability 1.1 or higher. |
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or later
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Bandwidth Test 
This is a simple test program to measure the memcopy bandwidth of the GPU. It currently is capable of measuring device to device copy bandwidth, host to device copy bandwidth for pageable and page-locked memory, and device to host copy bandwidth for pageable and page-locked memory. |
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or later
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Scan 
This example demonstrates an efficient CUDA implementation of parallel prefix sum, also known as "scan". Given an array of numbers, scan computes a new array in which each element is the sum of all the elements before it in the input array. |
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or later
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Scan of Large Arrays 
This example demonstrates an efficient CUDA implementation of parallel prefix sum (also known as "scan") for arbitrary-sized arrays. Given an array of numbers, scan computes a new array in which each element is the sum of all the elements before it in the input array. |
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or later
Download - Windows x86
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