Demo Data from VLDB 2026 / reviewers in the wild / expert
Zviad Metreveli
dblp:59/10954
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 61% Memory systems · 30% Storage systems · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Memory systems › cache management
cache partitioning |
0.1 | 1 | 2012 | CPHASH: a cache-partitioned hash table · PPoPP 2012 |
Parallel and multicore computing
concurrent data structures |
0.1 | 1 | 2012 | CPHASH: a cache-partitioned hash table · PPoPP 2012 |
Parallel and multicore computing › concurrent data structures
concurrent hashtable |
0.1 | 1 | 2012 | CPHASH: a cache-partitioned hash table · PPoPP 2012 |
Storage systems
key-value storage |
0.0 | 1 | 2012 | CPHASH: a cache-partitioned hash table · PPoPP 2012 |
Methods — techniques the papers use, named apart from their topics
message passing · 0.1lock-free synchronization · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | CPHASH: a cache-partitioned hash tableabstractCPHash is a concurrent hash table for multicore processors. CPHash partitions its table across the caches of cores and uses message passing to transfer lookups/inserts to a partition. CPHash's message passing avoids the need for locks, pipelines batches of asynchronous messages, and packs multiple messages into a single cache line transfer. Experiments on a 80-core machine with 2 hardware threads per core show that CPHash has ~1.6x higher throughput than a hash table implemented using fine-grained locks. An analysis shows that CPHash wins because it experiences fewer cache misses and its cache misses are less expensive, because of less contention for the on-chip interconnect and DRAM. CPServer, a key/value cache server using CPHash, achieves ~5% higher throughput than a key/value cache server that uses a hash table with fine-grained locks, but both achieve better throughput and scalability than memcached. The throughput of CPHash and CPServer also scale near-linearly with the number of cores. Zviad Metreveli, Nickolai Zeldovich, M. Frans Kaashoek |
PPoPP | 1 |