T
Thomas F. Wenisch
Researcher at University of Michigan
Publications - 161
Citations - 10765
Thomas F. Wenisch is an academic researcher from University of Michigan. The author has contributed to research in topics: Shared memory & Uniform memory access. The author has an hindex of 48, co-authored 156 publications receiving 9495 citations. Previous affiliations of Thomas F. Wenisch include Carnegie Mellon University & Google.
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Proceedings ArticleDOI
PowerNap: eliminating server idle power
TL;DR: The PowerNap concept, an energy-conservation approach where the entire system transitions rapidly between a high-performance active state and a near-zero-power idle state in response to instantaneous load, is proposed and the Redundant Array for Inexpensive Load Sharing (RAILS) is introduced.
Proceedings Article
Foreshadow: extracting the keys to the intel SGX kingdom with transient out-of-order execution
Jo Van Bulck,Marina Minkin,Ofir Weisse,Daniel Genkin,Baris Kasikci,Frank Piessens,Mark Silberstein,Thomas F. Wenisch,Yuval Yarom,Raoul Strackx +9 more
TL;DR: This work presents Foreshadow, a practical software-only microarchitectural attack that decisively dismantles the security objectives of current SGX implementations and develops a novel exploitation methodology to reliably leak plaintext enclave secrets from the CPU cache.
Proceedings ArticleDOI
SMARTS: accelerating microarchitecture simulation via rigorous statistical sampling
TL;DR: The Sampling Microarchitecture Simulation (SMARTS) framework is presented as an approach to enable fast and accurate performance measurements of full-length benchmarks and accelerates simulation by selectively measuring in detail only an appropriate benchmark subset.
Proceedings ArticleDOI
Disaggregated memory for expansion and sharing in blade servers
Kevin Lim,Jichuan Chang,Trevor Mudge,Parthasarathy Ranganathan,Steven K. Reinhardt,Thomas F. Wenisch +5 more
TL;DR: It is demonstrated that memory disaggregation can provide substantial performance benefits (on average 10X) in memory constrained environments, while the sharing enabled by the solutions can improve performance-per-dollar by up to 57% when optimizing memory provisioning across multiple servers.
Proceedings ArticleDOI
Power management of online data-intensive services
David Meisner,Christopher M. Sadler,Luiz Andre Barroso,Wolf-Dietrich Weber,Thomas F. Wenisch +4 more
TL;DR: This work evaluates the applicability of active and idle low-power modes to reduce the power consumed by the primary server components (processor, memory, and disk), while maintaining tight response time constraints, particularly on 95th-percentile latency.