Locality Prediction for Oblivious Clients

Oblivious Computation with Data Locality

Oblivious RAM compilers, introduced by Goldreich and Ostrovsky [JACM’96], compile any RAM program into one that is “memory-oblivious” (i.e., the access pattern to the memory is independent of the input). All previous ORAM schemes, however, completely break the locality of data accesses (by shuffling the data to pseudorandom positions in memory). In this work, we initiate the study of locality-f...

The Physics of No-Bit-Commitment: Generalized Quantum Non-Locality Versus Oblivious Transfer

An Oblivious Parallel RAM with O(logN) Parallel Runtime

Oblivious RAM (ORAM) is a cryptographic primitive that allows a client to access memory locations from a server without revealing its access patterns. Oblivious Parallel RAM (OPRAM) is a PRAM counterpart of Oblivious RAM, i.e., it allows m clients that trust each other to simultaneously access data from a server without revealing their access patterns. The best known OPRAM scheme [1, 2] achieve...

Cache oblivious matrix multiplication using an element ordering based on the Peano curve

One of the keys to tap the full performance potential of current hardware is the optimal utilisation of cache memory. Cache oblivious algorithms are designed to inherently benefit from any underlying hierarchy of caches, but do not need to know about the exact structure of the cache. In this paper, we present a cache oblivious algorithm for matrix multiplication. The algorithm uses a block recu...

Locality Aware Work-Stealing based Scheduling in Hybrid CPU-GPU Clusters

We study work-stealing based scheduling on a cluster of nodes with CPUs and GPUs. In particular, we evaluate locality aware scheduling in the context of distributed shared memory style programming, where the user is oblivious to data placement. Our runtime maintains a distributed map of data resident on various nodes and uses it to estimate the affinity of work to different nodes to guide sched...