An empirical evaluation of High-Level Synthesis languages and tools for database acceleration

High Level Synthesis (HLS) languages and tools are emerging as the most promising technique to make FPGAs more accessible to software developers. Nevertheless, picking the most suitable HLS for a certain class of algorithms depends on requirements such as area and throughput, as well as on programmer experience. In this paper, we explore the different trade-offs present when using a representative set of HLS tools in the context of Database Management Systems (DBMS) acceleration. More specifically, we conduct an empirical analysis of four representative frameworks (Bluespec SystemVerilog, Altera OpenCL, LegUp and Chisel) that we utilize to accelerate commonly-used database algorithms such as sorting, the median operator, and hash joins. Through our implementation experience and empirical results for database acceleration, we conclude that the selection of the most suitable HLS depends on a set of orthogonal characteristics, which we highlight for each HLS framework.Peer ReviewedPostprint (author’s final draft

Good approximate quantum LDPC codes from spacetime circuit Hamiltonians

We study approximate quantum low-density parity-check (QLDPC) codes, which are approximate quantum error-correcting codes specified as the ground space of a frustration-free local Hamiltonian, whose terms do not necessarily commute. Such codes generalize stabilizer QLDPC codes, which are exact quantum error-correcting codes with sparse, low-weight stabilizer generators (i.e. each stabilizer generator acts on a few qubits, and each qubit participates in a few stabilizer generators). Our investigation is motivated by an important question in Hamiltonian complexity and quantum coding theory: do stabilizer QLDPC codes with constant rate, linear distance, and constant-weight stabilizers exist? We show that obtaining such optimal scaling of parameters (modulo polylogarithmic corrections) is possible if we go beyond stabilizer codes: we prove the existence of a family of $[[N,k,d,\varepsilon]]$ approximate QLDPC codes that encode $k = \widetilde{\Omega}(N)$ logical qubits into $N$ physical qubits with distance $d = \widetilde{\Omega}(N)$ and approximation infidelity $\varepsilon = \mathcal{O}(1/\textrm{polylog}(N))$. The code space is stabilized by a set of 10-local noncommuting projectors, with each physical qubit only participating in $\mathcal{O}(\textrm{polylog} N)$ projectors. We prove the existence of an efficient encoding map, and we show that arbitrary Pauli errors can be locally detected by circuits of polylogarithmic depth. Finally, we show that the spectral gap of the code Hamiltonian is $\widetilde{\Omega}(N^{-3.09})$ by analyzing a spacetime circuit-to-Hamiltonian construction for a bitonic sorting network architecture that is spatially local in $\textrm{polylog}(N)$ dimensions.Comment: 51 pages, 13 figure

A Novel Hybrid Quicksort Algorithm Vectorized using AVX-512 on Intel Skylake

The modern CPU's design, which is composed of hierarchical memory and SIMD/vectorization capability, governs the potential for algorithms to be transformed into efficient implementations. The release of the AVX-512 changed things radically, and motivated us to search for an efficient sorting algorithm that can take advantage of it. In this paper, we describe the best strategy we have found, which is a novel two parts hybrid sort, based on the well-known Quicksort algorithm. The central partitioning operation is performed by a new algorithm, and small partitions/arrays are sorted using a branch-free Bitonic-based sort. This study is also an illustration of how classical algorithms can be adapted and enhanced by the AVX-512 extension. We evaluate the performance of our approach on a modern Intel Xeon Skylake and assess the different layers of our implementation by sorting/partitioning integers, double floating-point numbers, and key/value pairs of integers. Our results demonstrate that our approach is faster than two libraries of reference: the GNU \emph{C++} sort algorithm by a speedup factor of 4, and the Intel IPP library by a speedup factor of 1.4.Comment: 8 pages, research pape

Algebraic study of generalization and redundancy of the bitonic sorter.

Qian Zhengfeng.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 127-129).Abstracts in English and Chinese.Chapter Chapter 1 --- Groundwork --- p.1Chapter 1.1 --- Introduction --- p.1Chapter 1.2 --- Exchange Patterns --- p.5Chapter 1.3 --- Multistage Networks --- p.9Chapter 1.3.1 --- Multistage Networks --- p.9Chapter 1.3.2 --- Banyan-type Networks --- p.11Chapter 1.4 --- Networks of Sorting Cells --- p.15Chapter 1.5 --- Symbolic Representation and Matrix Representation --- p.19Chapter 1.5.1 --- Symbolic Representation of a Multistage Interconnection Network --- p.19Chapter 1.5.2 --- Symbolic Representation of a Network of Sorting Cells --- p.21Chapter 1.5.3 --- Matrix Representation of a Network of Sorting Cells --- p.22Chapter 1.6 --- Summary --- p.24Chapter Chapter 2 --- Construction of Generalized Bitonic Sorters by Merging Rotated Monotonic Sequences --- p.25Chapter 2.1 --- Merging Networks --- p.25Chapter 2.1.1 --- Recursive 2-stage Construction --- p.26Chapter 2.1.2 --- UC/CU Non-blocking Switches --- p.35Chapter 2.1.3 --- Circular Sorters and Merging Networks --- p.41Chapter 2.2 --- Construction of Generalized Bitonic Sorters --- p.48Chapter 2.2.1 --- Bitonic Ar-sorters and Bitonic Dr-sorters --- p.48Chapter 2.2.2 --- Algorithms for Construction of Generalized Bitonic Sorters by Merging Rotated Monotonic Sequences --- p.51Chapter 2.3 --- Summary --- p.73Chapter Chapter 3 --- Construction of Generalized Bitonic Sorters by Cross-k Cell Rearrangement --- p.74Chapter 3.1 --- Cross-k Cell Rearrangement on a Multistage Network --- p.74Chapter 3.1.1 --- Intra-stage Cell Rearrangement --- p.74Chapter 3.1.2 --- Equivalence of Networks --- p.77Chapter 3.1.3 --- Cross-k Cell Rearrangement --- p.80Chapter 3.2 --- Construction of Generalized Bitonic Sorters --- p.85Chapter 3.3 --- Summary --- p.99Chapter Chapter 4 --- Redundancy of the Bitonic Network --- p.100Chapter 4.1 --- Counting of Identified Generalized Bitonic Sorters --- p.100Chapter 4.2 --- Redundancy of the Bitonic Network --- p.110Epilogue --- p.112Appendix C Program for Exhaustive Search of 8×8 Generalized Bitonic Sorters --- p.113References --- p.12

Improving the performance of bubble sort using a modified diminishing increment sorting

Sorting involves rearranging information into either ascending or descending order. There are many sorting algorithms, among which is Bubble Sort. Bubble Sort is not known to be a very good sorting algorithm because it is beset with redundant comparisons. However, efforts have been made to improve the performance of the algorithm. With Bidirectional Bubble Sort, the average number of comparisons is slightly reduced and Batcher’s Sort similar to Shellsort also performs significantly better than Bidirectional Bubble Sort by carrying out comparisons in a novel way so that no propagation of exchanges is necessary. Bitonic Sort was also presented by Batcher and the strong point of this sorting procedure is that it is very suitable for a hard-wired implementation using a sorting network. This paper presents a meta algorithm called Oyelami’s Sort that combines the technique of Bidirectional Bubble Sort with a modified diminishing increment sorting. The results from the implementation of the algorithm compared with Batcher’s Odd-Even Sort and Batcher’s Bitonic Sort showed that the algorithm performed better than the two in the worst case scenario. The implication is that the algorithm is faster