Lecture 18: GPU Computing with thrust and cub.

Lecture Summary

  • Last time

    • A three-stop journey noted in the evolution of the CUDA memory model

      • Z-C accesses on the host; the UVA milestone; the unified memory model that allowed to use of managed memory

  • Today

    • GPU computing, from a distance (via thrust & CUB)


  • Motivation

    • Increase programmer productivity

    • Do not sacrifice execution speed

  • What is thrust?

    • A template library for parallel computing on GPU and CPU

    • Heavy use of C++ containers

    • Provides ready-to-use algorithms

Namespaces, containers, iterators

  • To avoid name collisions, use thrust vs. std namespaces

  • 2 vector containers: host_vector and device_vector

    • Just like those in the C++ STL

    • Manage both host & device memory

    • Auto allocation & deallocation

  • Iterators: Act like pointers for vector containers

    • Can be converted to raw containers

    • Raw pointers can also be wrapped with device_ptr


  • Element-wise operations

    • for_each, transform, gather, scatter

    • Example: SAXPY, functor using transform

  • Reductions

    • reduce, inner_product, reduce_by_key

  • Prefix sums (scans)

    • inclusive_scan, inclusive_scan_by_key

  • Sorting

    • sort, stable_sort, sort_by_key

General transformations. Zipping & fusing

  • Zipping

    • Takes in multiple distinct sequences, zips into unique sequence of tuples

  • Fusing

    • Just like zipping, but it's for reorganizing computation (instead of data) for efficient thrust processing

    • Increases the arithmetic intensity

Thrust example: Processing rainfall data

Not covered in class


  • CUB: CUDA UnBound

  • thrust is built on top of CUB

  • What CUB does

    • Parallel primitives

      • Warp-wide "collective" primitives

      • Block-wide "collective" primitives

      • Device-wide primitives

    • Utilities

      • Fancy iterators

      • Thread and thread block I/O

      • PTX intrinsics

      • Device, kernel, and storage management

Last updated