Entries filed under “Tools”

Multicore is everywhere from mobile devices to the datacenter. Enter ParaSail, a new programming language designed by SofCheck CTO Tucker Taft.

ParaSail uses a number of other tricks, some that draw on languages developed in the late 1980s and early 1990s for supercomputers—machines running many individual computer chips networked together. “The design of the language itself is essentially complete,” says Taft, who presented details of the language on Wednesday at the O’Reilly Open Source Convention. “The first version of the compiler will be released in the next month or so.” The language will work on Windows, Mac, and Linux computers.

It’s always tough to get traction with a new language, but Microsoft and Intel are reportedly putting $20 million into adapting existing languages for multicore processors, so ParaSail will have its work cut out for it. Read the Full Story.

Microsoft’s Satnam Singh writes about the company’s new Accelerator System, which allows certain kinds of data-parallel descriptions to be written once and then executed on three different targets: GPUs, multicore processors using SSE3 vector instructions, and FPGA circuits.

In general we cannot hope to devise one language or system for programming heterogeneous systems that allows us to compile a single source into efficient implementations on wildly different computing elements such as CPUs, GPUs, and FPGAs. Such parallel-performance portability is difficult to achieve. If the problem domain is sufficiently constrained, however, it is possible to achieve good parallel performance from a single source description. Accelerator achieves this by constraining the data types used for parallel programming (to whole arrays that cannot be explicitly indexed) and by providing a restricted set of parallel array access operations (e.g., in order, in reverse, with a stride, shifted, transposed).

Read the Full Story or Download Microsoft Accelerator.

In this extensive post, Computer Scientist and blogger JLouis goes the extra mile to dissect the Erlang programming language, urging the reader to go in with the realization that concurrency and parallelism are different beasts:

Note however, while Erlang is not a parallel language, its runtime is rather excellent at forcing out parallelism of existing concurrent programs. So when we say Erlang is parallel, we say that Erlang is parallel in a specific way! The recent years have seen much work in Erlang/OTP on making the runtime concurrently parallel and we are reaping the benefits. The reason can be found in the simple observation that a Erlang program has thousands of processes which gives thousands of executable threads of control. Since you have more than one thread of control, and communication between them is largely asynchronous, you have all the opportunity for a parallel speedup.

Read the Full Story.

The GPU Science blog has a post on Intel’s new high performance SPMD Compiler:

“ispc is a new compiler for “single program, multiple data” (SPMD) programs. Under the SPMD model, the programmer writes a program that mostly appears to be a regular serial program, though the execution model is actually that a number of program instances execute in parallel on the hardware. ispc compiles a C-based SPMD programming language to run on the SIMD units of CPUs; it frequently provides a 3x or more speedup on CPUs with 4-wide SSE units, without any of the difficulty of writing intrinsics code.

Read the Full Story.

This week PathScale announced that the EKOPath 4 Compiler Suite is now available as an open source project and free download for Linux, FreeBSD and Solaris. Called “some of the best C/C++/Fortran compilers on the market” by Scalable Informatics CEO Joe Landman, the release includes documentation and the complete development stack, including compiler, debugger, assembler, runtimes and standard libraries. EKOPath is the product of years of ongoing development, representing one of the industries highest performance Intel 64 and AMD C, C++ and Fortran compilers.

“This is an exciting announcement because it allows PathScale’s world-class compilers to be accessible to a much larger community of compiler users. The enlarged user base will benefit PathScale, and in turn promote more community participation in the continued development of PathScale’s products.” says Fred Chow, PathScale Chief Scientist.

PathScale will continue to provide full paid support for EKOPath and offer additional support options for AMD’s Open64 compiler. Read the Full Story.

Aater Suleman at the Future Chips blog looks at how to choose the best task size at run-time for parallel programming. He analyzes the trade-offs and explains some recent advances in work-queues that minimize their overhead.

“To maximize concurrency, all threads should be programmed to complete their work at the same time. Balancing the load among threads requires the programmers to predict the latency of each task, which is often impossible due to unpredictable OS/hardware effects. Consequently, programmers split the work into small tasks and use work-queues to distribute the work dynamically. Work-queues exist in many programming paradigms like Grand Central Dispatch, Intel TBB, Cilk, Open MP, etc. While work-queues improve load-balancing, they introduce the overhead of adding and removing tasks to and from the work-queue. Thus, if each individual task is too small, the work-queue overhead becomes prohibitive and if its too long then there is risk of imbalance.”

Read the Full Story.