Speculative execution is an optimization technique where a computer system performs some task that may not be needed. Work is done before it is known whether it is actually needed, so as to prevent a delay that would have to be incurred by doing the work after it is known that it is needed. If it turns out the work was not needed after all, most changes made by the work are reverted and the results are ignored.
John Leroy Hennessy is an American computer scientist who is chairperson of Alphabet Inc. (Google). Hennessy is one of the founders of MIPS Technologies and Atheros, and also the tenth President of Stanford University. Hennessy announced that he would step down in the summer of 2016. He was succeeded as president by Marc Tessier-Lavigne. Marc Andreessen called him "the godfather of Silicon Valley."
Michael J. Flynn is an American professor emeritus at Stanford University.
Thread Level Speculation (TLS), also known as Speculative Multi-threading, or Speculative Parallelization, is a technique to speculatively execute a section of computer code that is anticipated to be executed later in parallel with the normal execution on a separate independent thread. Such a speculative thread may need to make assumptions about the values of input variables. If these prove to be invalid, then the portions of the speculative thread that rely on these input variables will need to be discarded and squashed. If the assumptions are correct the program can complete in a shorter time provided the thread was able to be scheduled efficiently.
Maurice Peter Herlihy is an American computer scientist active in the field of multiprocessor synchronization. Herlihy has contributed to areas including theoretical foundations of wait-free synchronization, linearizable data structures, applications of combinatorial topology to distributed computing, as well as hardware and software transactional memory. He is the An Wang Professor of Computer Science at Brown University, where he has been a member of the faculty since 1994.
In cache coherency protocol literature, Write-Once was the first MESI protocol defined. It has the optimization of executing write-through on the first write and a write-back on all subsequent writes, reducing the overall bus traffic in consecutive writes to the computer memory. It was first described by James R. Goodman in (1983). Cache coherence protocols are an important issue in Symmetric multiprocessing systems, where each CPU maintains a cache of the memory.
James Richard "Jim" Goodman retired as professor of computer science at the University of Auckland in Auckland, New Zealand, and emeritus professor at the University of Wisconsin–Madison.
Kathryn S. McKinley is an American computer scientist noted for her research on compilers, runtime systems, and computer architecture. She is also known for her leadership in broadening participation in computing. McKinley was co-chair of CRA-W from 2011 to 2014.
Margaret Martonosi is an American computer scientist who is currently the Hugh Trumbull Adams '35 Professor of Computer Science at Princeton University. Martonosi is noted for her research in computer architecture and mobile computing with a particular focus on power-efficiency.
Susan J. Eggers is an American computer scientist noted for her research on computer architecture and compilers.
Stanford DASH was a cache coherent multiprocessor developed in the late 1980s by a group led by Anoop Gupta, John L. Hennessy, Mark Horowitz, and Monica S. Lam at Stanford University. It was based on adding a pair of directory boards designed at Stanford to up to 16 SGI IRIS 4D Power Series machines and then cabling the systems in a mesh topology using a Stanford-modified version of the Torus Routing Chip. The boards designed at Stanford implemented a directory-based cache coherence protocol allowing Stanford DASH to support distributed shared memory for up to 64 processors. Stanford DASH was also notable for both supporting and helping to formalize weak memory consistency models, including release consistency. Because Stanford DASH was the first operational machine to include scalable cache coherence, it influenced subsequent computer science research as well as the commercially available SGI Origin 2000. Stanford DASH is included in the 25th anniversary retrospective of selected papers from the International Symposium on Computer Architecture and several computer science books, has been simulated by the University of Edinburgh, and is used as a case study in contemporary computer science classes.
An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator or computer system designed to accelerate artificial intelligence and machine learning applications, including artificial neural networks and computer vision. Typical applications include algorithms for robotics, Internet of Things, and other data-intensive or sensor-driven tasks. They are often manycore designs and generally focus on low-precision arithmetic, novel dataflow architectures or in-memory computing capability. As of 2024, a typical AI integrated circuit chip contains tens of billions of MOSFETs.
Cache prefetching is a technique used by computer processors to boost execution performance by fetching instructions or data from their original storage in slower memory to a faster local memory before it is actually needed. Most modern computer processors have fast and local cache memory in which prefetched data is held until it is required. The source for the prefetch operation is usually main memory. Because of their design, accessing cache memories is typically much faster than accessing main memory, so prefetching data and then accessing it from caches is usually many orders of magnitude faster than accessing it directly from main memory. Prefetching can be done with non-blocking cache control instructions.
Babak Falsafi is an Iranian-American computer scientist specializing in computer architecture and digital platform design. He is the founding director of EcoCloud at EPFL, an industrial/academic consortium investigating efficient and intelligent data-centric technologies. He is a professor in the School of Computer and Communication Sciences at EPFL. Prior to that he was a professor of electrical and computer engineering at Carnegie Mellon University, and an assistant professor of electrical and computer engineering at Purdue University. He holds a bachelor's degree in computer science, a bachelor's degree in electrical and computer engineering with distinctions from SUNY Buffalo, and a master's degree and PhD in computer science from University Wisconsin - Madison.
ACM SIGARCH is the Association for Computing Machinery's Special Interest Group on computer architecture, a community of computer professionals and students from academia and industry involved in research and professional practice related to computer architecture and design. The organization sponsors many prestigious international conferences in this area, including the International Symposium on Computer Architecture (ISCA), recognized as the top conference in this area since 1975. Together with IEEE Computer Society's Technical Committee on Computer Architecture (TCCA), it is one of the two main professional organizations for people working in computer architecture.
The Association for Computing Machinery SIGARCH Alan D. Berenbaum Distinguished Service Award is given for outstanding service in the field of computer architecture and design.
Mark D. Hill is a computer scientist and professor at the University of Wisconsin–Madison. He has been cited over 27,000 times.
Norman Paul Jouppi is an American electrical engineer and computer scientist.
Timothy M. Pinkston is an American computer engineer, researcher, educator and administrator whose work is focused in the area of computer architecture. He holds the George Pfleger Chair in Electrical and Computer Engineering and is a Professor of Electrical and Computer Engineering at University of Southern California (USC). He also serves in an administrative role as Vice Dean for Faculty Affairs at the USC Viterbi School of Engineering.
Trevor Mudge is a computer scientist, academic and researcher. He is the Bredt Family Chair of Computer Science and Engineering, and Professor of Electrical Engineering and Computer Science at the University of Michigan.
