doc: graph computation

Signed-off-by: Sijie Shen <[email protected]>

README.md

@@ -66,10 +66,10 @@ To adapt to rich workload flexibility, GART proposes transparent data model conv
 We provide a sample definition file called [rgmapping-ldbc.yaml](vegito/test/schema/rgmapping-ldbc.yaml).
 
 ### Efficient Dynamic Graph Storage
-To ensure the performance of graph analytical processing (GAP), GART proposes an efficient dynamic graph storage with good locality that stems from key insights into online graph computation, including:
+To ensure the performance of graph computation, GART proposes an efficient dynamic graph storage with good locality that stems from key insights into online graph computation, including:
 1. an efficient and mutable compressed sparse row (CSR) representation to guarantee the locality of scanning edges;
 2. a coarse-grained MVCC to reduce the temporal and spatial overhead of versioning;
-3. a flexible property storage to efficiently run various GAP workloads.
+3. a flexible property storage to efficiently run various graph computation workloads.
 
 Please refer to [our paper](https://www.usenix.org/conference/atc23/presentation/shen) for specific technical implementation details.
 

converter/flags.cc

@@ -30,12 +30,12 @@ DEFINE_bool(use_logs_per_epoch, true, "use_logs_per_epoch.");
 DEFINE_string(etcd_endpoint, "127.0.0.1:2379", "etcd endpoint.");
 DEFINE_string(etcd_prefix, "", "etcd prefix.");
 
-DEFINE_int32(subgraph_num, 1, "Number of subgraphs for GAP workloads.");
+DEFINE_int32(subgraph_num, 1, "Number of subgraphs.");
 
 DEFINE_int32(checkpoint_interval, 10, "Checkpoint interval in minutes.");
 DEFINE_string(checkpoint_dir, "/tmp/checkpoint", "Checkpoint directory.");
 
 DEFINE_bool(enable_bulkload, false, "Enable bulkload from existing data.");
 
 DEFINE_int32(num_threads, 4, "Number of threads for processing logs.");
-DEFINE_int32(max_queue_size, 20480, "Max queue size for logs.");
+DEFINE_int32(max_queue_size, 20480, "Max queue size for logs.");

docs/documentation/design/architecture.rst

@@ -75,13 +75,13 @@ We provide a sample definition file called `RGMappings`_.
 Efficient Dynamic Graph Storage
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-To ensure the performance of graph analytical processing (GAP), GART proposes an efficient dynamic graph storage with good locality that stems from key insights into online graph computation workloads, including:
+To ensure the performance of graph computation, GART proposes an efficient dynamic graph storage with good locality that stems from key insights into online graph computation workloads, including:
 
 1. an efficient and mutable compressed sparse row (CSR) representation to guarantee the locality of scanning edges;
 
 2. a coarse-grained MVCC to reduce the temporal and spatial overhead of versioning;
 
-3. flexible property storage to efficiently run various GAP workloads.
+3. flexible property storage to efficiently run various graph computation workloads.
 
 Service-Oriented Deployment Model
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

docs/documentation/getting-started/intro-content.rst

@@ -58,13 +58,13 @@ We provide a sample definition file called `RGMappings`_.
 Efficient Dynamic Graph Storage
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-To ensure the performance of graph analytical processing (GAP), GART proposes an efficient dynamic graph storage with good locality that stems from key insights into online graph computation workloads, including:
+To ensure the performance of graph computation, GART proposes an efficient dynamic graph storage with good locality that stems from key insights into online graph computation workloads, including:
 
 1. an efficient and mutable compressed sparse row (CSR) representation to guarantee the locality of scanning edges;
 
 2. a coarse-grained MVCC to reduce the temporal and spatial overhead of versioning;
 
-3. flexible property storage to efficiently run various GAP workloads.
+3. flexible property storage to efficiently run various graph computation workloads.
 
 Service-Oriented Deployment Model
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^