Latest News
Paper Accepted at DAMON 2023
A. Bernhardt, A. Koch, I. Petrov. pimDB: From Main-Memory DBMS to Processing-In-Memory DBMS-Engines on Intelligent Memories. In Proc. DAMON 2023.
In this paper, we introduce pimDB and provide an initial comparison of processor-centric and PIM-DBMS approaches under different aspects, such as scalability and parallelism, cache-awareness, or PIM-specific compute/bandwidth tradeoffs.
Abstract:
In this paper, we introduce pimDB and provide an initial comparison of processor-centric and PIM-DBMS approaches under different aspects, such as scalability and parallelism, cache-awareness, or PIM-specific compute/bandwidth tradeoffs.
Congrats "Dr." Riegger!
DBlab congratulates Christian Riegger on the successful defence of his dissertation "Multi-version Indexing for large Datasets with high-rate continuous Insertions" . So congrats on the next level, Christian!
Best Paper Award EDBT'23
Our paper bloomRF: On Performing Range-Queries in Bloom-Filters with Piecewise-Monotone Hash Functions and Prefix Hashing has been awarded a Best Paper Award at (EDBT 2023)
We are extremely happy about the recognition and wish to thank the committee for considering our work.HiPEAC 2022 Paper Award
Our paper S. Tamimi, F. Stock, A. Bernhardt, I. Petrov, A. Koch. An Evaluation of Using CCIX for Cache-Coherent Host-FPGA Interfacing. In Proc. FCCM 2022. has been awarded a HiPEAC 2022 Paper Award.
Congrats "Dr." Vincon!
DBlab congratulates Tobias Vincon on the successful defence of his dissertation "Data-Intensive Systems on Modern Hardware: leveraging near-data processing to counter the growth of data" . What a journey it has been. So congrats "Dr." Vincon!
Paper Accepted at EDBT
B. Moessner, C. Riegger, A. Bernhardt, I. Petrov. bloomRF: On Performing Range-Queries in Bloom-Filters with Piecewise-Monotone Hash Functions and Prefix Hashing. In Proc. EDBT 2023.
We introduce bloomRF as a unified point-range filter that extends Bloom-filters with range-queries.
Abstract:
We introduce bloomRF as a unified PRF that extends BFs with range- lookups. We propose novel prefix hashing to encode range information in the hash-code of the key, and novel PMHF for fast lookups and #fewer memory accesses. We describe basic bloomRF that is simple and tuning-free, and propose optimizations for han- dling larger ranges. bloomRF has near-optimal space- and constant query-complexity and outperforms existing PRF by up to 4x.