In the News
Stay up-to-date on what is happening at TMT
See what the industry is saying about the self-parallelizing SequenceL technology. We invite you to follow along with the successes as awareness of TMT grows throughout the industry.
March 2, 2017
Further strengthening its commitment to support all popular multicore platforms, Texas Multicore Technologies (TMT) today announced that the high performance SequenceL™ functional programming language and auto-parallelizing compiler now fully support ARM® processors running the Linux operating system, including 32 and 64-bit architectures.
January 16, 2017
Texas Multicore Technologies (TMT) today announced the company has has released a major new version of its SequenceL functional programming language and auto-parallelizing compiler and tool set. Adds Free Community Edition, Performance, Expanded Platform Support
November 9, 2016
Texas Multicore Technologies (TMT) today announced the company has joined the OpenPOWER Foundation, an open development community based on the POWER microprocessor architecture.
June 26, 2016
Finding a way to optimally parallelize linear code for multi-processor platforms has been a holy grail of computer science for many years. The challenge is that we think linearly and design algorithms in the same way, but then want to speed up our analysis by adding parallelism to the algorithms we have already designed.
January 31, 2015
The SequenceL development environment is tailored for multicore and many-core programming applications. SequenceL provides a powerful functional programming language and auto-parallelizing tools for tuning code for multicore platforms.
December 17, 2014
As multiprocessor chips become more prevalent, the ability to program them efficiently has become more important. There’s no doubt that mainstream programming languages are not great for writing parallel programs.
August 20, 2014
If you design the software right, you can really take advantage of multicore systems. It’s the classic hammer and nail problem – choosing the appropriate tool for the job.
February 7, 2014
Parallelism is in the natural order of things. The industrial revolution, i.e., automated manufacturing, was about pipeline parallelism. And the supermarket check-outs, another kind of parallelism, can be thought of as segmentation parallelism – an array of parallel processors that segment the workload. We knew about parallelism before there were any computers.
January 31, 2014
Project eliminates many steps in multicore programming, allowing developers to write to C++ and automatically distribute to any number of cores. SequenceL is a declarative, functional language that’s geared to multicore programming; it provides automatic parallelization, and the compiler outputs C++ code.
Parallelizing complex code efficiently across multiple processor cores gets to be a task beyond human ability. SequenceL is a high-level language that can automatically analyze and output parallel code as C++ and OpenCL to run on a variety of today’s multicore processors.
SequenceL has been found to discover all potential parallelisms automatically in relatively complex algorithms (involving multiple threads), and thus shows the potential to relieve more of the programmer’s cognitive load as the problem grows in complexity.
Implementing parallelism in powerful accelerated processors can be a complex task. Software parallelization can ease the process and quickly help manage growing and complex M2M wireless industrial networks.
Dr. Robin Bloor introduces a new software development language and environment, named SequenceL, that is specifically targeted at writing software that runs efficiently on parallel hardware. This white paper examines the technology, describing in outline how it works, why there is a need for it and how well it performs in parallel environments.
What is SequenceL and where did it come from? This article briefly describes TMT’s revolutionary automatic parallelization technology and how it arose from research by NASA and Texas Tech University. The basic architecture and initial test results show a real solution to the parallelization and multicore utilization bottle-neck.
This research feature is a good overview of SequenceL. It begins with a review of abstractions in procedural, object oriented, and functional programming to introduce the SequenceL abstraction that shields the user from the need to know how the parallel programming is implemented. It includes many examples and reviews work done with NASA and other customers.