https://cppcon.org/ https://github.com/CppCon/CppCon2020 --- Performance is one of the chief reasons why many C++ programmers love the language. In the past, Moore's Law meant that our programs ran faster every year. Now that Dennard scaling has ended, C++ programmers have to work harder to get high performance for their applications. In this talk, I'll first discuss some of the significant and surprising challenges facing C++ programmers trying to achieve high performance on modern hardware platforms: performance is far less stable and predictable than you might think! I'll present some experimental evidence that strongly suggests we can't count on compiler optimizations to help us out of this hole: in particular, I'll show -- using a new experimental methodology -- that the difference between clang's -O2 and -O3 optimization levels is essentially indistinguishable from noise.
Since compiler optimizations have run out of steam, we need better profiling support, especially for modern concurrent, multi-threaded applications. I'll talk about a new approach to profiling, which I call "causal profiling". Causal profiling lets programmers optimize for throughput or latency, and which pinpoints and accurately predicts the impact of optimizations. It works by running performance experiments, based on the idea of "virtual speedups". We've built a causal profiler called Coz, which now ships as part of standard Linux distros, and which also works for C++ and Rust (there's even a Java version). Using it, we find that Coz can unlock previously unknown optimization opportunities. Guided by Coz, we improved the performance of Memcached (9%), SQLite (25%), and accelerated six other 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!).
--- 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, where he co-directs the PLASMA @ UMass lab. He graduated with a Ph.D. 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, three 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 Distinguished Member in 2018. 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, and was Program Chair for PLDI 2016.
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