Performance clearly matters to users. For example, the most common software update on the AppStore is "Bug fixes and performance enhancements." Now that Moore's Law has ended, programmers have to work hard to get high performance for their applications. But why is performance hard to deliver?
I will first explain why current approaches to evaluating and optimizing performance don't work. I'll show how complicated performance has become on modern systems, and how compiler optimizations have essentially run out of steam.
Next, I'll introduce two radically new performance profilers that guide programmers directly to the code they need to change to improve application performance. The first is Coz, a new "causal profiler" for C/C++/Rust (with a Java version as well) that lets programmers optimize for throughput or latency, and which pinpoints and accurately predicts the impact of optimizations via what we call "virtual speedup" experiments. Coz's approach unlocks previously unknown optimization opportunities. Guided by Coz, we improved the performance of applications by as much as 68%; in most cases, this involved modifying less than 10 lines of code and took under half an hour (without any prior understanding of the programs!). Coz now ships as part of standard Linux distros (apt install coz-profiler).
The second is Scalene, a "scripting-language aware" profiler for Python (with other scripting languages to come). Scalene runs orders of magnitude faster than other profilers while delivering far more detailed information -- information that's especially valuable to Python programmers. Via a combination of sampling, inference, and disassembly of byte-codes, Scalene efficiently and precisely attributes execution time and memory usage to Python, which developers can optimize, or library code, which they cannot. Its novel sampling memory allocator efficiently reports line-level memory consumption and trends with low overhead, helping developers reduce footprints and identify leaks. Finally, Scalene reports a new metric, copy volume, that helps developers root out insidious copying costs across the Python/library boundary, which can drastically degrade performance. Scalene is available on PyPi (pip install scalene).
Emery Berger is a Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst, the flagship campus of the UMass system. He graduated with a PhD in Computer Science from the University of Texas at Austin in 2002. Professor Berger has been a Visiting Scientist at Microsoft Research and at the Universitat Politècnica de Catalunya (UPC)/Barcelona Supercomputing Center (BSC). Professor Berger’s research spans programming languages, runtime systems, and operating systems, with a particular focus on systems that transparently improve reliability, security, and performance. He and his collaborators have created a number of influential software systems including Hoard, a fast and scalable memory manager that accelerates multithreaded applications (used by companies including British Telecom, Cisco, Crédit Suisse, Reuters, Royal Bank of Canada, SAP, and Tata, and on which the Mac OS X memory manager is based); DieHard, an error-avoiding memory manager that directly influenced the design of the Windows 7 Fault-Tolerant Heap; and DieHarder, a secure memory manager that was an inspiration for hardening changes made to the Windows 8 heap.
His honors include a Microsoft Research Fellowship, an NSF CAREER Award, a Lilly Teaching Fellowship, the Distinguished Artifact Award for PLDI 2014, the Most Influential Paper Award at OOPSLA 2012, the Most Influential Paper Award at PLDI 2016, the ASPLOS 2019 Influential Paper Award, five CACM Research Highlights, a Google Research Award, a Microsoft SEIF Award, and Best Paper Awards at FAST, OOPSLA, and SOSP; he was named an ACM Fellow in 2019. Professor Berger is currently serving his second term as an elected member of the SIGPLAN Executive Committee; he served for a decade (2007-2017) as Associate Editor of the ACM Transactions on Programming Languages and Systems, was Program Chair for PLDI 2016, and is co-Program Chair of ASPLOS 2021.
