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v0.1.1

Index

  • What is Tensor Comprehensions?
    • Example of using TC with framework
    • Tensor Comprehension Notation
    • Examples of TC
      • Simple matrix-vector
      • Simple 2-D convolution (no stride, no padding)
      • Simple 2D max pooling
  • Semantics
    • Types
    • Data Layout
    • Variable Scoping
    • Implied Reductions and operators
    • Size Expressions
    • Statements
    • Expressions
    • Grammar
  • Range Inference
    • The Range Inference Algorithm
    • Preconditions
    • Worked Examples
      • Inverted indexing
      • Strided indexing with constant stride
      • Strided indexing with offsets
      • Strided indexing with dynamic stride
      • Constant fill using an exists clause
  • Relation to Halide
    • Use of Halide in TC
  • Mapping Options
    • How to choose starting mapping options?
    • Options API
    • Defaults provided
    • Available options
    • Impact on Performance
    • Possible compiler issues
  • Autotuner
    • Parameters for Autotuning
    • Caching
  • Performance of TC

Machine Learning with TC

  • Positioning of TC in ML Software stacks
    • Implications of ML Framework Integration
      • One TC function one kernel
      • No Variable Allocations
      • Graph Level
    • Minimal information to write ML layers concisely
      • C-style loops
      • Halide
      • TC
      • Matrix Languages
  • Integrating TC with ML framework
    • Step 1: DLpack support in framework
    • Step 2: Integrating TC
  • Coding Conventions
    • Use indices named after parameters
    • Prefix reduction index names with r_
    • Filter non-rectangular regions with data-dependencies
    • Prefix gradient tensors names with d_
    • A more complex example

PyTorch Integration

  • Getting Started
    • Installation
    • Example
  • Python API
    • High-level API
    • Low-level API
    • Caching and Configuration
  • Writing TC operations
    • Example
    • Specifying MappingOptions
    • Loading from cache
    • Autotuning
    • Fixed TC, varying input sizes
    • Pseudo-templating
    • Built-in Functions
    • More examples
  • Autograd with TC
  • Debugging
    • Example usage
    • Printing TC generated CUDA code
  • Frequently Asked Questions
    • TC language
      • How are temporary variables handled in TC?
      • Can I re-use a temporary variable?
    • Autotuner
      • At the start of a new generation, I see higher kernel runtimes, Why?
      • I sometimes see fluctuations in the best kernel time, why?
      • How do I stop autotuning early and save cache?

Installation

  • Installation Guide
    • Conda installation
    • Build from source
      • Prerequisites
      • Conda from scratch (first time configuration)
      • Activate conda in your current terminal
      • Build TC with dependencies supplied by conda
      • Test locally
    • Advanced / development mode installation
      • Optional dependencies
      • Cudnn version 7.1 in Caffe2 / dev mode
  • Installation in the Google Colaboratory environment
    • Step 1: Create new Notebook in the Google Research Colaboratory
    • Step 2: Create a new Code Cell, with the following code
    • Step 3: Use TC normally, from Python/Torch environment

Paper

  • Tech Report

Support

  • Contacts
    • Bugs and features
    • Mailing list
    • Contributions
    • Slack channel
Tensor Comprehensions
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