![]() Renaming a file in the Project Outline will now work correctly if the file does not yet exist. The Reset to Head Git operation now works as expected. The development environment received an assortment of bug fixes. If users wish to enforce an alternative wrapping column, the value can be set in the Appearance and Behavior Options window under the "Language Features category. The editor is aware of pre-existing continuations as well, and will attempt to maintain consistent formatting. By default, when a line exceeds the language's line limit, Simply Fortran will now automatically wrap the line, inserting the appropriate syntactical markers where necessary. The code editor now supports automatic line continuation for both fixed- and free-format Fortran source code. Quicker and more flexible than using "Untitled" files, Scratch Pads provide a quick and simple code storage method. Scratch Pads are temporary files completely managed by Simply Fortran for quickly storing code segments, evaluating algorithms, or simply taking notes. The development environment now features "Scratch Pads," accessible via the File menu or by pressing F4 (or Shift+F4 to open an existing Scratch Pad). This release introduces new features and bug fixes for the development environment and Windows compiler. The research that led to the development of Scalene was supported by the National Science Foundation.Simply Fortran version 3.28 is now available for all supported platforms from Approximatrix. Scalene is already in wide use and has been downloaded more than 750,000 times since its public unveiling on GitHub. “Future improvements in speed will come less from better hardware and more from faster, more efficient programming.” “Computers are no longer getting faster,” says Berger. “It’s not just a speedometer telling you how fast or slow your car is going, it tells you if you could be going faster, why your speed is affected, and what you can do to get up to maximum speed.” The Future of Programming and Scalene’s Impact “This is an actionable dashboard,” says Berger. Once Scalene has identified where Python is having trouble keeping up, it then uses AI-leveraging the same technology underpinning ChatGPT-to suggest ways to optimize individual lines, or even groupings of code. It focuses on three key areas-the CPU, GPU, and memory usage-that are responsible for the majority of Python’s sluggish speed. “Scalene first teases out where your program is wasting time,” Berger says. At best, they indicate that a region of code is slow, and leave it to the programmer to figure out what, if anything, can be done.īerger’s team, which included UMass computer science graduate students Sam Stern and Juan Altmayer Pizzorno, built Scalene to be the first profiler that not only precisely identifies inefficiencies in Python code, but also uses AI to suggest how the code can be improved. Unfortunately, existing profilers do surprisingly little to help Python programmers. Programmers have long known this, and to help fight Python’s inefficiency, they can use tools called “profilers.” Profilers run programs and then pinpoint why and which parts are slow. UMass Amherst Professor of Computer Science Emery Berger. There are many different programming languages-C++, Fortran, and Java are some of the more well-known ones-but, in recent years, one language has become nearly ubiquitous: Python. Programs written with Python are notoriously slow-up to 60,000 times slower than code written in other programming languages-and Scalene works to efficiently identify exactly where Python is lagging, allowing programmers to troubleshoot and streamline their code for higher performance. Their development Scalene, an open-source tool for dramatically speeding up the programming language Python, circumvents hardware issues limiting computer processing speeds.Ī team of computer scientists at the University of Massachusetts Amherst, led by Emery Berger, recently unveiled a prize-winning Python profiler called Scalene. This development gains significance as the future leans towards better programming for speed improvements. Unlike traditional profilers, Scalene uses AI to both identify and suggest fixes for code inefficiencies. Researchers from the University of Massachusetts Amherst introduced Scalene, a cutting-edge Python profiler.
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