Marcadores
replication
performance
consistency
distributed
fault-tolerance
protocols
linearizability
strong
eurosys
rdma
scale
asplos
ndsi
sosp
osdi
locality
transactions
fast
low-latency
invalidations
hermes
skew
fully
numa
out
scale-out
transformations
actions
map
large
spark
rdd
reduce
consensus
almost-local
alr
faults
crash
asynchronous
reads
local
linearizable
cap
impossibility
theorem
l2aw
coherence
concurrency
viva
thesis
phd
systems
database
serializability
strict
available
reliable
throughput
poster
fault
datastore
propagation
early
broadcast
paxos
latency
sequential consistency
caching
symmetric
writes
sequential
2018
eurosys18
hot
ccnuma
cc
lstm
2017
machine
deep
neural
isca
tpu
cost
accelerator
google
convolutional
hardware
learning
networks
asic
cnn
tensor
model
critical
frameworks
paper
data
deán
matei
hadoop
jeff
processing
review
big
yarn
jargons
big data
master
slave
issues
rdds
shuffle
framework
goals
bottleneck
Ver mais
Apresentações
(8)Documentos
(1)Gostaram
(3)Zeus Locality aware distributed transaction upload.pptx
YongraeJo
•
Há 2 anos
Zeus: Locality-aware Distributed Transactions [Eurosys '21 presentation]
Antonios Katsarakis
•
Há 3 anos
Kite: efficient and available release consistency for the datacenter
Vasilis Gavrielatos
•
Há 4 anos
Marcadores
replication
performance
consistency
distributed
fault-tolerance
protocols
linearizability
strong
eurosys
rdma
scale
asplos
ndsi
sosp
osdi
locality
transactions
fast
low-latency
invalidations
hermes
skew
fully
numa
out
scale-out
transformations
actions
map
large
spark
rdd
reduce
consensus
almost-local
alr
faults
crash
asynchronous
reads
local
linearizable
cap
impossibility
theorem
l2aw
coherence
concurrency
viva
thesis
phd
systems
database
serializability
strict
available
reliable
throughput
poster
fault
datastore
propagation
early
broadcast
paxos
latency
sequential consistency
caching
symmetric
writes
sequential
2018
eurosys18
hot
ccnuma
cc
lstm
2017
machine
deep
neural
isca
tpu
cost
accelerator
google
convolutional
hardware
learning
networks
asic
cnn
tensor
model
critical
frameworks
paper
data
deán
matei
hadoop
jeff
processing
review
big
yarn
jargons
big data
master
slave
issues
rdds
shuffle
framework
goals
bottleneck
Ver mais