Document Updates

The main updates to the documents are summarised below. In addition there will have been many incremental improvements and corrections.

July 2021

A new white paper on Graphcore’s AI-Float technology with hardware support for mixed-precision and stochastic rounding.

• AI-Float™ - Mixed Precision Arithmetic for AI: A Hardware Perspective

June 2021

SDK 2.1 release

For full details of all the changes in this release, see the SDK 2.1.0 Release Notes.

Other changes

• The Graphcore GitHub repositories have been split into a section for tutorials and examples to help you get started, and another with sample applications for the IPU.

• New tutorial on using the PopVision analysis library (libpva)

• New example of using PopDist for distributed training

• New technical note published on using the availableMemoryProportion option to optimise memory use: Optimising Temporary Memory Usage for Convolutions and Matmuls on the IPU

• Updated TensorFlow 1 tutorial on half precision training:

  • an improved section on loss scaling

  • a new section on how to avoid numerical issues (overflow, underflow, unstable operations)

  • and an additional example using the IPUEstimator

• Updated PyTorch tutorial on half precision training:

  • a new section on numerical stability (loss scaling, stochastic rounding)

  • a section on debugging floating-point exceptions

  • a section on PopTorch tracing

• Updated Poplar profiling tutorial (tutorial 4):

  • code for the IPU Model and for running on hardware (previously only the IPU Model could be used)

  • an improved section on out-of-memory errors

  • an improved section on navigating a profile generated by PopVision Graph Analyser

May 2021

• Published a new technical note on the implementation and performance of BERT-Large on Graphcore IPU-POD systems: Pre-Training and Fine-Tuning BERT for the IPU

• The V-IPU Administrator Guide has been updated with a new chapter on monitoring application metrics using Prometheus and InfluxDB.

April 2021

• A new technical note has been published with an overview of how to add custom operations in PyTorch, TensorFlow and PopART: Creating Custom Operations for the IPU.

• The technical note Model parallelism with TensorFlow: sharding and pipelining was revised to be consistent with SDK 2.0, and with the addition of content on pipelining Keras models in TensorFlow 2.

• The “Writing custom operations” chapter in the TensorFlow 1 and TensorFlow 2 user guides has been completely rewritten,

• New tutorials have been added on using half and mixed-precision floating point in PopTorch and TensorFlow 1, and efficient data loading with PopTorch

March 2021

Hardware documents

• The IPU-POD Direct Attach build and test guide has been updated.

• Published the IPU-POD16 Direct Attach Datasheet.

Updates since SDK 2.0

Since the SDK release, the following documents have been updated:

• The Graphcore Command Line Tools document has been updated to 1.0.51. This adds a description of the information returned by the gc-info --tile-overview option and documents the new gc-exchangewritetest command.

• The Targeting the IPU from TensorFlow 1 has been updated with an improved explanation of the role of XLA.

SDK 2.0 release

For full details of all the changes in this release, see the SDK 2.0.0 Release Notes.

The main documentation changes are:

• Additions to:

  • Targeting the IPU from TensorFlow 1

  • Targeting the IPU from TensorFlow 2

  • PyTorch for the IPU: User Guide

• New: PopDist and PopRun: User Guide documents the tool for running distributed programs and the associated PopDist library.

• New and updated functions in the Poplar and PopLibs API Reference:

  • New libraries:

    • poplar/DebugContext.hpp

    • poplar/TensorRearranger.hpp

    • poplin/Cholesky.hpp

    • poplin/TriangularSolve.hpp

    • popnn/CTCLoss.hpp

    • popnn/LogSoftmax.hpp

    • popnn/Rnn.hpp

    • popops/CollectiveTypes.hpp

    • popops/SequenceSlice.hpp

    • popops/SortOrder.hpp

    • popops/TopK.hpp

    • popsparse/MatMulParams.hpp

    • poputil/OptionParsing.hpp

    • poputil/TensorMetaData.hpp

  • Changes:

    • Renamed poplar/CycleEstimateFunc.hpp to poplar/PerfEstimateFunc.hpp

    • Renamed popops/Collectives.hpp to popops/TensorCollectives.hpp

• The PopVision trace instrumentation (PVTI) and PopVision analysis (PVA) libraries are now included in the in Poplar docs.

  • PopVision trace instrumentation library in the Poplar User Guide

  • PopVision trace instrumentation library (PVTI) API

  • PopVision analysis C++ API

  • PopVision Analysis Python API

Other changes

• There is now a contents page listing the examples and tutorials available on GitHub.

• The IPU-M2000 DA system has been renamed to Getting Started with IPU-POD4 DA and IPU-POD16 DA and updated.

November 2020

This includes the release of Poplar SDK 1.4, the IPU-M2000, the IPU-POD reference design and the supporting software tools.

• Poplar SDK 1.4

  • Updates for new features in the SDK 1.4 release (see the SDK release notes for details of changes and new features in the SDK)

  • PopART: New chapter on writing custom ops <popart-user-guide:custom_ops>

  • PopTorch: extended PyTorch for the IPU: User Guide & new GitHub tutorial & how-to video

  • Keras: Introduction to using Keras in TensorFlow 2 on the IPU

  • TensorFlow: Added documentation and GitHub tutorial on Graph Recompilation in TensorFlow 2

  • PopVision: PopVision User Guide for the System Analyser and the trace instrumentation library (libpvti)

  • Additional video tutorials: Using Data Feeds & Training Loops, Evaluating Batch Sizes for IPUs and Fundamentals of BSP

• New and updated documents for IPU-POD64 reference design

  • Getting Started with IPU-POD Systems

  • IPU-POD64 Data Centre Checklist

  • IPU-POD64 Reference Design: Build and Test Guide

  • IPU-POD64 Installation & Integration Guide

  • IPU-POD64 Datasheet

• New documents for IPU-M2000 direct attach

  • ipu-m2000-getting-started:index

  • ipu-m2000-build-test:index

  • IPU-Machine: M2000 Datasheet

• Documents for hardware support tools:

  • V-IPU Administrator Guide

  • V-IPU User Guide

  • BMC User Guide