Efficient Memory Allocation for Increased Performance

Turbocharge your C++ code: Memory management is a foundational part of building parallel programs that perform nice and fast and seamless. Find out how Threading Building Blocks Memory Allocator can meet the need.
  • What Development C++ Intel
  • When 20 June 2019 from 02:00 AM to 03:00 AM (Australia/Melbourne / UTC1000)
  • Where Webinar
  • Web Visit external website
  • Add event to calendar iCal

Modern computing solutions have seen monster-scale increases in the volume of raw data that must be collected and processed from sensors and actuators.

It’s a phenomenon further emphasized by the emergence of smart, autonomous systems that require visual cognition and control under strict latency requirements.

Result? The need for efficient number crunching—using increasingly powerful devices—is growing at the IoT edge. But … bandwidth is still at a premium and workloads collected at the edge vary significantly based on industry.

Enter Intel® System Studio 2019 with Python* language support.

Join Intel’s Tudor Panu for a comprehensive tour of the new software suite, including:

  • How its integration of Python makes it the ideal solution for quick data processing needs and analytics using a variety of Intel® Software Performance Libraries
  • An overview of Python support in the tool suite (Pydev plugin support)
  • Exploring included code samples and techniques for Python application development
  • IDE synergy with the Intel® Distribution for Python*

Register now.

Get the software

  • Intel® System Studio 2019 with Python* support
  • Intel® Distribution for Python*
  • Intel® Performance Libraries

    Managing computer memory is a fundamental consideration when developing and optimizing any software application. It’s a job handled by the memory allocator—a program that ensures free blocks of memory are available at the right time and in the right amount for efficient application performance.

    It’s not an easy task, particularly for parallel applications that expect fast allocation and de-allocation while also demanding the allocator return memory that’s “hot” in the CPU cache, avoid hitting cache associativity limits, prevent false sharing, and keep memory consumption modest.

    A common result? Performance bottlenecks.

    The Threading Building Blocks (TBB) scalable memory allocator can solve these problems and improve performance of parallel programs.

    Join Intel Software Engineer Nikita Ponomarev to find out how, including:

  • Main principles of memory allocator design
  • How to use the TBB memory allocator
  • How to tune the scalable allocator behavior and control memory consumption

Register now.

Get the software
Download Threading Building Blocks today—one of five free Intel® Performance Libraries.