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2,382 results on '"Hill, Mark"'

3. Characterizing the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER

Author

Lucas, Olivia, Ward, Sophia, Zaidi, Rija, Bunkum, Abigail, Frankell, Alexander M., Moore, David A., Hill, Mark S., Liu, Wing Kin, Marinelli, Daniele, Lim, Emilia L., Hessey, Sonya, Naceur-Lombardelli, Cristina, Rowan, Andrew, Purewal-Mann, Sukhveer Kaur, Zhai, Haoran, Dietzen, Michelle, Ding, Boyue, Royle, Gary, Aparicio, Samuel, McGranahan, Nicholas, Jamal-Hanjani, Mariam, Kanu, Nnennaya, Swanton, Charles, and Zaccaria, Simone

Published
2024
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4. Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Author

Hynds, Robert E., Huebner, Ariana, Pearce, David R., Hill, Mark S., Akarca, Ayse U., Moore, David A., Ward, Sophia, Gowers, Kate H. C., Karasaki, Takahiro, Al Bakir, Maise, Wilson, Gareth A., Pich, Oriol, Martínez-Ruiz, Carlos, Hossain, A. S. Md Mukarram, Pearce, Simon P., Sivakumar, Monica, Ben Aissa, Assma, Grönroos, Eva, Chandrasekharan, Deepak, Kolluri, Krishna K., Towns, Rebecca, Wang, Kaiwen, Cook, Daniel E., Bosshard-Carter, Leticia, Naceur-Lombardelli, Cristina, Rowan, Andrew J., Veeriah, Selvaraju, Litchfield, Kevin, Crosbie, Philip A. J., Dive, Caroline, Quezada, Sergio A., Janes, Sam M., Jamal-Hanjani, Mariam, Marafioti, Teresa, McGranahan, Nicholas, and Swanton, Charles

Published
2024
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9. Author Correction: The evolution of lung cancer and impact of subclonal selection in TRACERx

Author

Frankell, Alexander M., Dietzen, Michelle, Al Bakir, Maise, Lim, Emilia L., Karasaki, Takahiro, Ward, Sophia, Veeriah, Selvaraju, Colliver, Emma, Huebner, Ariana, Bunkum, Abigail, Hill, Mark S., Grigoriadis, Kristiana, Moore, David A., Black, James R. M., Liu, Wing Kin, Thol, Kerstin, Pich, Oriol, Watkins, Thomas B. K., Naceur-Lombardelli, Cristina, Cook, Daniel E., Salgado, Roberto, Wilson, Gareth A., Bailey, Chris, Angelova, Mihaela, Bentham, Robert, Martínez-Ruiz, Carlos, Abbosh, Christopher, Nicholson, Andrew G., Le Quesne, John, Biswas, Dhruva, Rosenthal, Rachel, Puttick, Clare, Hessey, Sonya, Lee, Claudia, Prymas, Paulina, Toncheva, Antonia, Smith, Jon, Xing, Wei, Nicod, Jerome, Price, Gillian, Kerr, Keith M., Naidu, Babu, Middleton, Gary, Blyth, Kevin G., Fennell, Dean A., Forster, Martin D., Lee, Siow Ming, Falzon, Mary, Hewish, Madeleine, Shackcloth, Michael J., Lim, Eric, Benafif, Sarah, Russell, Peter, Boleti, Ekaterini, Krebs, Matthew G., Lester, Jason F., Papadatos-Pastos, Dionysis, Ahmad, Tanya, Thakrar, Ricky M., Lawrence, David, Navani, Neal, Janes, Sam M., Dive, Caroline, Blackhall, Fiona H., Summers, Yvonne, Cave, Judith, Marafioti, Teresa, Herrero, Javier, Quezada, Sergio A., Peggs, Karl S., Schwarz, Roland F., Van Loo, Peter, Miedema, Daniël M., Birkbak, Nicolai J., Hiley, Crispin T., Hackshaw, Allan, Zaccaria, Simone, Jamal-Hanjani, Mariam, McGranahan, Nicholas, and Swanton, Charles

Published
2024
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10. A Primer on Memory Consistency and Cache Coherence, Second Edition

Author

Nagarajan, Vijay, Sorin, Daniel J., Hill, Mark D., and Wood, David A.

Subjects
Open Access, thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFC Electronics: circuits and components, thema EDItEUR::U Computing and Information Technology::UY Computer science::UYF Computer architecture and logic design
Abstract

Many modern computer systems, including homogeneous and heterogeneous architectures, support shared memory in hardware. In a shared memory system, each of the processor cores may read and write to a single shared address space. For a shared memory machine, the memory consistency model defines the architecturally visible behavior of its memory system. Consistency definitions provide rules about loads and stores (or memory reads and writes) and how they act upon memory. As part of supporting a memory consistency model, many machines also provide cache coherence protocols that ensure that multiple cached copies of data are kept up-to-date. The goal of this primer is to provide readers with a basic understanding of consistency and coherence. This understanding includes both the issues that must be solved as well as a variety of solutions. We present both high-level concepts as well as specific, concrete examples from real-world systems. This second edition reflects a decade of advancements since the first edition and includes, among other more modest changes, two new chapters: one on consistency and coherence for non-CPU accelerators (with a focus on GPUs) and one that points to formal work and tools on consistency and coherence. This is an open access book. This is an open access book.

Published
2020
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11. Pond: CXL-Based Memory Pooling Systems for Cloud Platforms

Author

Li, Huaicheng, Berger, Daniel S., Novakovic, Stanko, Hsu, Lisa, Ernst, Dan, Zardoshti, Pantea, Shah, Monish, Rajadnya, Samir, Lee, Scott, Agarwal, Ishwar, Hill, Mark D., Fontoura, Marcus, and Bianchini, Ricardo

Subjects
Computer Science - Operating Systems, Computer Science - Performance
Abstract

Public cloud providers seek to meet stringent performance requirements and low hardware cost. A key driver of performance and cost is main memory. Memory pooling promises to improve DRAM utilization and thereby reduce costs. However, pooling is challenging under cloud performance requirements. This paper proposes Pond, the first memory pooling system that both meets cloud performance goals and significantly reduces DRAM cost. Pond builds on the Compute Express Link (CXL) standard for load/store access to pool memory and two key insights. First, our analysis of cloud production traces shows that pooling across 8-16 sockets is enough to achieve most of the benefits. This enables a small-pool design with low access latency. Second, it is possible to create machine learning models that can accurately predict how much local and pool memory to allocate to a virtual machine (VM) to resemble same-NUMA-node memory performance. Our evaluation with 158 workloads shows that Pond reduces DRAM costs by 7% with performance within 1-5% of same-NUMA-node VM allocations., Comment: Update affiliations

Published
2022

13. A National Discovery Cloud: Preparing the US for Global Competitiveness in the New Era of 21st Century Digital Transformation

Author

Foster, Ian, Lopresti, Daniel, Gropp, Bill, Hill, Mark D., and Schuman, Katie

Subjects
Computer Science - Computers and Society
Abstract

The nature of computation and its role in our lives have been transformed in the past two decades by three remarkable developments: the emergence of public cloud utilities as a new computing platform; the ability to extract information from enormous quantities of data via machine learning; and the emergence of computational simulation as a research method on par with experimental science. Each development has major implications for how societies function and compete; together, they represent a change in technological foundations of society as profound as the telegraph or electrification. Societies that embrace these changes will lead in the 21st Century; those that do not, will decline in prosperity and influence. Nowhere is this stark choice more evident than in research and education, the two sectors that produce the innovations that power the future and prepare a workforce able to exploit those innovations, respectively. In this article, we introduce these developments and suggest steps that the US government might take to prepare the research and education system for its implications., Comment: A Computing Community Consortium (CCC) white paper, 6 pages

Published
2021

14. Advancing Computing's Foundation of US Industry & Society

Author

Conte, Thomas M., Foster, Ian T., Gropp, William, and Hill, Mark D.

Subjects
Computer Science - Computers and Society, Computer Science - Hardware Architecture
Abstract

While past information technology (IT) advances have transformed society, future advances hold even greater promise. For example, we have only just begun to reap the changes from artificial intelligence (AI), especially machine learning (ML). Underlying IT's impact are the dramatic improvements in computer hardware, which deliver performance that unlock new capabilities. For example, recent successes in AI/ML required the synergy of improved algorithms and hardware architectures (e.g., general-purpose graphics processing units). However, unlike in the 20th Century and early 2000s, tomorrow's performance aspirations must be achieved without continued semiconductor scaling formerly provided by Moore's Law and Dennard Scaling. How will one deliver the next 100x improvement in capability at similar or less cost to enable great value? Can we make the next AI leap without 100x better hardware? This whitepaper argues for a multipronged effort to develop new computing approaches beyond Moore's Law to advance the foundation that computing provides to US industry, education, medicine, science, and government. This impact extends far beyond the IT industry itself, as IT is now central for providing value across society, for example in semi-autonomous vehicles, tele-education, health wearables, viral analysis, and efficient administration. Herein we draw upon considerable visioning work by CRA's Computing Community Consortium (CCC) and the IEEE Rebooting Computing Initiative (IEEE RCI), enabled by thought leader input from industry, academia, and the US government., Comment: A Computing Community Consortium (CCC) white paper, 4 pages

Published
2021

17. Antibodies against endogenous retroviruses promote lung cancer immunotherapy

Author

Ng, Kevin W., Boumelha, Jesse, Enfield, Katey S. S., Almagro, Jorge, Cha, Hongui, Pich, Oriol, Karasaki, Takahiro, Moore, David A., Salgado, Roberto, Sivakumar, Monica, Young, George, Molina-Arcas, Miriam, de Carné Trécesson, Sophie, Anastasiou, Panayiotis, Fendler, Annika, Au, Lewis, Shepherd, Scott T. C., Martínez-Ruiz, Carlos, Puttick, Clare, Black, James R. M., Watkins, Thomas B. K., Kim, Hyemin, Shim, Seohee, Faulkner, Nikhil, Attig, Jan, Veeriah, Selvaraju, Magno, Neil, Ward, Sophia, Frankell, Alexander M., Al Bakir, Maise, Lim, Emilia L., Hill, Mark S., Wilson, Gareth A., Cook, Daniel E., Birkbak, Nicolai J., Behrens, Axel, Yousaf, Nadia, Popat, Sanjay, Hackshaw, Allan, Hiley, Crispin T., Litchfield, Kevin, McGranahan, Nicholas, Jamal-Hanjani, Mariam, Larkin, James, Lee, Se-Hoon, Turajlic, Samra, Swanton, Charles, Downward, Julian, and Kassiotis, George

Published
2023
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18. The evolution of non-small cell lung cancer metastases in TRACERx

Author

Al Bakir, Maise, Huebner, Ariana, Martínez-Ruiz, Carlos, Grigoriadis, Kristiana, Watkins, Thomas B. K., Pich, Oriol, Moore, David A., Veeriah, Selvaraju, Ward, Sophia, Laycock, Joanne, Johnson, Diana, Rowan, Andrew, Razaq, Maryam, Akther, Mita, Naceur-Lombardelli, Cristina, Prymas, Paulina, Toncheva, Antonia, Hessey, Sonya, Dietzen, Michelle, Colliver, Emma, Frankell, Alexander M., Bunkum, Abigail, Lim, Emilia L., Karasaki, Takahiro, Abbosh, Christopher, Hiley, Crispin T., Hill, Mark S., Cook, Daniel E., Wilson, Gareth A., Salgado, Roberto, Nye, Emma, Stone, Richard Kevin, Fennell, Dean A., Price, Gillian, Kerr, Keith M., Naidu, Babu, Middleton, Gary, Summers, Yvonne, Lindsay, Colin R., Blackhall, Fiona H., Cave, Judith, Blyth, Kevin G., Nair, Arjun, Ahmed, Asia, Taylor, Magali N., Procter, Alexander James, Falzon, Mary, Lawrence, David, Navani, Neal, Thakrar, Ricky M., Janes, Sam M., Papadatos-Pastos, Dionysis, Forster, Martin D., Lee, Siow Ming, Ahmad, Tanya, Quezada, Sergio A., Peggs, Karl S., Van Loo, Peter, Dive, Caroline, Hackshaw, Allan, Birkbak, Nicolai J., Zaccaria, Simone, Jamal-Hanjani, Mariam, McGranahan, Nicholas, and Swanton, Charles

Published
2023
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19. The evolution of lung cancer and impact of subclonal selection in TRACERx

Author

Frankell, Alexander M., Dietzen, Michelle, Al Bakir, Maise, Lim, Emilia L., Karasaki, Takahiro, Ward, Sophia, Veeriah, Selvaraju, Colliver, Emma, Huebner, Ariana, Bunkum, Abigail, Hill, Mark S., Grigoriadis, Kristiana, Moore, David A., Black, James R. M., Liu, Wing Kin, Thol, Kerstin, Pich, Oriol, Watkins, Thomas B. K., Naceur-Lombardelli, Cristina, Cook, Daniel E., Salgado, Roberto, Wilson, Gareth A., Bailey, Chris, Angelova, Mihaela, Bentham, Robert, Martínez-Ruiz, Carlos, Abbosh, Christopher, Nicholson, Andrew G., Le Quesne, John, Biswas, Dhruva, Rosenthal, Rachel, Puttick, Clare, Hessey, Sonya, Lee, Claudia, Prymas, Paulina, Toncheva, Antonia, Smith, Jon, Xing, Wei, Nicod, Jerome, Price, Gillian, Kerr, Keith M., Naidu, Babu, Middleton, Gary, Blyth, Kevin G., Fennell, Dean A., Forster, Martin D., Lee, Siow Ming, Falzon, Mary, Hewish, Madeleine, Shackcloth, Michael J., Lim, Eric, Benafif, Sarah, Russell, Peter, Boleti, Ekaterini, Krebs, Matthew G., Lester, Jason F., Papadatos-Pastos, Dionysis, Ahmad, Tanya, Thakrar, Ricky M., Lawrence, David, Navani, Neal, Janes, Sam M., Dive, Caroline, Blackhall, Fiona H., Summers, Yvonne, Cave, Judith, Marafioti, Teresa, Herrero, Javier, Quezada, Sergio A., Peggs, Karl S., Schwarz, Roland F., Van Loo, Peter, Miedema, Daniël M., Birkbak, Nicolai J., Hiley, Crispin T., Hackshaw, Allan, Zaccaria, Simone, Jamal-Hanjani, Mariam, McGranahan, Nicholas, and Swanton, Charles

Published
2023
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20. Genomic–transcriptomic evolution in lung cancer and metastasis

Author

Martínez-Ruiz, Carlos, Black, James R. M., Puttick, Clare, Hill, Mark S., Demeulemeester, Jonas, Larose Cadieux, Elizabeth, Thol, Kerstin, Jones, Thomas P., Veeriah, Selvaraju, Naceur-Lombardelli, Cristina, Toncheva, Antonia, Prymas, Paulina, Rowan, Andrew, Ward, Sophia, Cubitt, Laura, Athanasopoulou, Foteini, Pich, Oriol, Karasaki, Takahiro, Moore, David A., Salgado, Roberto, Colliver, Emma, Castignani, Carla, Dietzen, Michelle, Huebner, Ariana, Al Bakir, Maise, Tanić, Miljana, Watkins, Thomas B. K., Lim, Emilia L., Al-Rashed, Ali M., Lang, Danny, Clements, James, Cook, Daniel E., Rosenthal, Rachel, Wilson, Gareth A., Frankell, Alexander M., de Carné Trécesson, Sophie, East, Philip, Kanu, Nnennaya, Litchfield, Kevin, Birkbak, Nicolai J., Hackshaw, Allan, Beck, Stephan, Van Loo, Peter, Jamal-Hanjani, Mariam, Swanton, Charles, and McGranahan, Nicholas

Published
2023
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21. Lung adenocarcinoma promotion by air pollutants

Author

Hill, William, Lim, Emilia L., Weeden, Clare E., Lee, Claudia, Augustine, Marcellus, Chen, Kezhong, Kuan, Feng-Che, Marongiu, Fabio, Evans, Jr, Edward J., Moore, David A., Rodrigues, Felipe S., Pich, Oriol, Bakker, Bjorn, Cha, Hongui, Myers, Renelle, van Maldegem, Febe, Boumelha, Jesse, Veeriah, Selvaraju, Rowan, Andrew, Naceur-Lombardelli, Cristina, Karasaki, Takahiro, Sivakumar, Monica, De, Swapnanil, Caswell, Deborah R., Nagano, Ai, Black, James R. M., Martínez-Ruiz, Carlos, Ryu, Min Hyung, Huff, Ryan D., Li, Shijia, Favé, Marie-Julie, Magness, Alastair, Suárez-Bonnet, Alejandro, Priestnall, Simon L., Lüchtenborg, Margreet, Lavelle, Katrina, Pethick, Joanna, Hardy, Steven, McRonald, Fiona E., Lin, Meng-Hung, Troccoli, Clara I., Ghosh, Moumita, Miller, York E., Merrick, Daniel T., Keith, Robert L., Al Bakir, Maise, Bailey, Chris, Hill, Mark S., Saal, Lao H., Chen, Yilun, George, Anthony M., Abbosh, Christopher, Kanu, Nnennaya, Lee, Se-Hoon, McGranahan, Nicholas, Berg, Christine D., Sasieni, Peter, Houlston, Richard, Turnbull, Clare, Lam, Stephen, Awadalla, Philip, Grönroos, Eva, Downward, Julian, Jacks, Tyler, Carlsten, Christopher, Malanchi, Ilaria, Hackshaw, Allan, Litchfield, Kevin, DeGregori, James, Jamal-Hanjani, Mariam, and Swanton, Charles

Published
2023
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22. Evolutionary characterization of lung adenocarcinoma morphology in TRACERx

Author

Karasaki, Takahiro, Moore, David A., Veeriah, Selvaraju, Naceur-Lombardelli, Cristina, Toncheva, Antonia, Magno, Neil, Ward, Sophia, Bakir, Maise Al, Watkins, Thomas B. K., Grigoriadis, Kristiana, Huebner, Ariana, Hill, Mark S., Frankell, Alexander M., Abbosh, Christopher, Puttick, Clare, Zhai, Haoran, Gimeno-Valiente, Francisco, Saghafinia, Sadegh, Kanu, Nnennaya, Dietzen, Michelle, Pich, Oriol, Lim, Emilia L., Martínez-Ruiz, Carlos, Black, James R. M., Biswas, Dhruva, Campbell, Brittany B., Lee, Claudia, Colliver, Emma, Enfield, Katey S. S., Hessey, Sonya, Hiley, Crispin T., Zaccaria, Simone, Litchfield, Kevin, Birkbak, Nicolai J., Cadieux, Elizabeth Larose, Demeulemeester, Jonas, Van Loo, Peter, Adusumilli, Prasad S., Tan, Kay See, Cheema, Waseem, Sanchez-Vega, Francisco, Jones, David R., Rekhtman, Natasha, Travis, William D., Hackshaw, Allan, Marafioti, Teresa, Salgado, Roberto, Le Quesne, John, Nicholson, Andrew G., McGranahan, Nicholas, Swanton, Charles, and Jamal-Hanjani, Mariam

Published
2023
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23. Opportunities and Challenges for Next Generation Computing

Author

Hager, Gregory D., Hill, Mark D., and Yelick, Katherine

Subjects
Computer Science - Computers and Society, Computer Science - Hardware Architecture
Abstract

Computing has dramatically changed nearly every aspect of our lives, from business and agriculture to communication and entertainment. As a nation, we rely on computing in the design of systems for energy, transportation and defense; and computing fuels scientific discoveries that will improve our fundamental understanding of the world and help develop solutions to major challenges in health and the environment. Computing has changed our world, in part, because our innovations can run on computers whose performance and cost-performance has improved a million-fold over the last few decades. A driving force behind this has been a repeated doubling of the transistors per chip, dubbed Moore's Law. A concomitant enabler has been Dennard Scaling that has permitted these performance doublings at roughly constant power, but, as we will see, both trends face challenges. Consider for a moment the impact of these two trends over the past 30 years. A 1980's supercomputer (e.g. a Cray 2) was rated at nearly 2 Gflops and consumed nearly 200 KW of power. At the time, it was used for high performance and national-scale applications ranging from weather forecasting to nuclear weapons research. A computer of similar performance now fits in our pocket and consumes less than 10 watts. What would be the implications of a similar computing/power reduction over the next 30 years - that is, taking a petaflop-scale machine (e.g. the Cray XK7 which requires about 500 KW for 1 Pflop (=1015 operations/sec) performance) and repeating that process? What is possible with such a computer in your pocket? How would it change the landscape of high capacity computing? In the remainder of this paper, we articulate some opportunities and challenges for dramatic performance improvements of both personal to national scale computing, and discuss some "out of the box" possibilities for achieving computing at this scale., Comment: A Computing Community Consortium (CCC) white paper, 7 pages

Published
2020

24. Nanotechnology-inspired Information Processing Systems of the Future

Author

Bryant, Randy, Hill, Mark, Kazior, Tom, Lee, Daniel, Liu, Jie, Nahrstedt, Klara, Narayanan, Vijay, Rabaey, Jan, Siegelmann, Hava, Shanbhag, Naresh, Verma, Naveen, and Wong, H. -S. Philip

Subjects
Computer Science - Computers and Society, Computer Science - Emerging Technologies
Abstract

Nanoscale semiconductor technology has been a key enabler of the computing revolution. It has done so via advances in new materials and manufacturing processes that resulted in the size of the basic building block of computing systems - the logic switch and memory devices - being reduced into the nanoscale regime. Nanotechnology has provided increased computing functionality per unit volume, energy, and cost. In order for computing systems to continue to deliver substantial benefits for the foreseeable future to society at large, it is critical that the very notion of computing be examined in the light of nanoscale realities. In particular, one needs to ask what it means to compute when the very building block - the logic switch - no longer exhibits the level of determinism required by the von Neumann architecture. There needs to be a sustained and heavy investment in a nation-wide Vertically Integrated Semiconductor Ecosystem (VISE). VISE is a program in which research and development is conducted seamlessly across the entire compute stack - from applications, systems and algorithms, architectures, circuits and nanodevices, and materials. A nation-wide VISE provides clear strategic advantages in ensuring the US's global superiority in semiconductors. First, a VISE provides the highest quality seed-corn for nurturing transformative ideas that are critically needed today in order for nanotechnology-inspired computing to flourish. It does so by dramatically opening up new areas of semiconductor research that are inspired and driven by new application needs. Second, a VISE creates a very high barrier to entry from foreign competitors because it is extremely hard to establish, and even harder to duplicate., Comment: A Computing Community Consortium (CCC) workshop report, 18 pages

Published
2020

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